Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1 - Introduction to DataScience
Posted by Superadmin on November 13 2019 00:14:29

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


01.1. A Practical Example What You Will Learn in This Course


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


01.2. What Does the Course Cover


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

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Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


02.1. Data Science and Business Buzzwords Why are there so many


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


02.2. Data Science and Business Buzzwords Why are there so many.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


02.3. What is the difference between Analysis and Analytics


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


02.4. What is the difference between Analysis and Analytics.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


02.5. Business Analytics, Data Analytics, and Data Science An Introduction


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


02.5.1 365_DataScience_Diagram.pdf


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


02.6. Business Analytics, Data Analytics, and Data Science An Introduction.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


02.7. Continuing with BI, ML, and AI


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


02.7.1 365_DataScience_Diagram.pdf


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


02.7.2 365_DataScience.png


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


02.8. Continuing with BI, ML, and AI


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


02.9. A Breakdown of our Data Science Infographic


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


02.9.1 365_DataScience.png


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


02.10. A Breakdown of our Data Science Infographic



The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


03.1. Applying Traditional Data, Big Data, BI, Traditional Data Science and ML


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


03.2. Applying Traditional Data, Big Data, BI, Traditional Data Science and ML.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


04.1. The Reason behind these Disciplines


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


04.2. The Reason behind these Disciplines.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


05.1. Techniques for Working with Traditional Data


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


05.2. Techniques for Working with Traditional Data.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


05.3. Real Life Examples of Traditional Data


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


05.4. Techniques for Working with Big Data


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


05.5. Techniques for Working with Big Data.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


05.6. Real Life Examples of Big Data


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


05.7. Business Intelligence (BI) Techniques


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


05.8. Business Intelligence (BI) Techniques.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


05.9. Real Life Examples of Business Intelligence (BI)


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


05.10. Techniques for Working with Traditional Methods


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


05.11. Techniques for Working with Traditional Methods.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


05.12. Real Life Examples of Traditional Methods


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


05.13. Machine Learning (ML) Techniques


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


05.14. Machine Learning (ML) Techniques.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


05.15. Types of Machine Learning


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


05.16. Types of Machine Learning.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


05.17. Real Life Examples of Machine Learning (ML)


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


05.18. Real Life Examples of Machine Learning (ML).html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


06.1. Necessary Programming Languages and Software Used in Data Science


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


06.2. Necessary Programming Languages and Software Used in Data Science.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


07.1. Finding the Job - What to Expect and What to Look for


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


07.2. Finding the Job - What to Expect and What to Look for.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


08.1. Debunking Common Misconceptions


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part1

with Iliya


08.2. Debunking Common Misconceptions.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01.Part 1 Introduction 02.The Field of Data Science - The Various Data Science Disciplines 03.The Field of Data Science - Connecting the Data Science Disciplines 04.The Field of Data Science - The Benefits of Each Discipline 05.The Field of Data Science - Popular Data Science Techniques 06.The Field of Data Science - Popular Data Science Tools 07.The Field of Data Science - Careers in Data Science 08.The Field of Data Science - Debunking Common Misconceptions