Digital Transformation for Tech Leaders

1h 4m • COURSE

Migrating to the cloud? Get an overview of cloud computing and the key concepts that you should consider when making a move to the cloud. There are three types of cloud solutions: software as a service, infrastructure as a service, and platform as a service. Instructor David Linthicum helps you evaluate these solutions, including Amazon Web Services, Google Cloud Platform, Salesforce.com, and Office 365, as well as the data and applications that are best suited to the cloud. He explains how to select a cloud provider and plan a migration, and reviews the security considerations and typical day-to-day operations and tools IT administrators need to keep their cloud-based infrastructure up and running.

Topics include: • Types of clouds: SaaS, IaaS, and PaaS • Identifying the data and applications to move to the cloud • Migrating planning • Selecting a provider • Cloud security • Cloud operations

1h 1m • COURSE

Are you new to cloud computing? If so, this course can help you bolster your cloud computing skillset by familiarizing you with the business and tech-related basics of creating a cloud architecture. Join cloud-computing luminary David Linthicum as he discusses what cloud architecture is and why a strong architecture is crucial. After covering the fundamentals, he moves on to identifying the business and technical requirements of building a cloud architecture, and goes over cloud parts and how to work from requirements to a solution. The course concludes by leading you through how to build your first architecture.

Topics include: • Cloud architecture basics • What problems need to be solved? • The "as is" and "to be" states • Cloud storage, CPUs, and databases • Building your first architecture

58m 44s • COURSE

State-of-the-art technology is changing the way we design for the cloud. New architectural patterns are emerging as a result of breakthroughs such as microservices, containers, and serverless computing. Want to know how these advanced concepts will affect your cloud strategy and solution? This platform-neutral course is targeted at IT professionals who already know the basics of architecting cloud solutions and wish to understand the impact of new technologies on their business. Learn how independently deployable, modular services—microservices—will affect the structure of your cloud-based applications; how serverless and composite architectures such as AWS Lambda and Azure Functions free up engineers to focus on features, not infrastructures; and how new high-performance solutions allow you to "lease" computing storage and power. Instructor David Linthicum also discusses DevOps integration and advanced architecture strategies, such as isolating change and volatility in a single domain.

Topics include: • Microservices and containers • Complex, disturbed, serverless, and composite architectures • DevOps integration • High-performance solutions

2h 12m • COURSE

Big data is big news. But what is big data, and how do we use it? Simply put, big data is data that, by virtue of its velocity, volume, or variety (the three Vs), cannot be easily stored or analyzed with traditional methods. Spreadsheets and relational databases just don't cut it with big data. In this course, Barton Poulson tells you the methods that do work, introducing all the techniques and concepts involved in capturing, storing, manipulating, and analyzing big data, including data mining and predictive analytics. He explains big data's relationship to data science, statistics, and programing; its uses in marketing, scientific research, and tools like Amazon's recommendation engine; and the ethical issues that lie behind its use.

Lynda.com is a PMI Registered Education Provider. This course qualifies for professional development units (PDUs). To view the activity and PDU details for this course, click here.

The PMI Registered Education Provider logo is a registered mark of the Project Management Institute, Inc.

1h 27m • COURSE

Computer-enhanced artificial intelligence (AI) has been around since the 1950s, but recent hardware innovations have reinvigorated the field. New sensors help machines have more accurate sight, hear sounds, and understand location. Powerful processors can help computers make complex decisions, sort through possibilities, plan outcomes, and learn from mistakes. The possibilities are thrilling; the implications are vast.

This course will introduce you to some of the key concepts behind artificial intelligence, including the differences between "strong" and "weak" AI. You'll see how AI has created questions around what it means to be intelligent and how much trust we should put in machines. Instructor Doug Rose explains the different approaches to AI, including machine learning and deep learning, and the practical uses for new AI-enhanced technologies. Plus, learn how to integrate AI with other technology, such as big data, and avoid some common pitfalls associated with programming AI.

Topics include:: • The history of AI • Machine learning • Technical approaches to AI • AI in robotics • Integrating AI with big data • Avoiding pitfalls

1h 4m • COURSE

Value estimation—one of the most common types of machine learning algorithms—can automatically estimate values by looking at related information. For example, a website can determine how much a house is worth based on the property's location and characteristics. In this project-based course, discover how to use machine learning to build a value estimation system that can deduce the value of a home. Follow Adam Geitgey as he walks through how to use sample data to build a machine learning model, and then use that model in your own programs. Although the project featured in this course focuses on real estate, you can use the same approach to solve any kind of value estimation problem with machine learning.

Topics include: • Setting up the development environment • Building a simple home value estimator • Finding the best weights automatically • Working with large data sets efficiently • Training a supervised machine learning model • Exploring a home value data set • Deciding how much data is needed • Preparing the features • Training the value estimator • Measuring accuracy with mean absolute error • Improving a system • Using the machine learning model to make predictions

1h 16m • COURSE

Many data science specialists are looking to pivot toward focusing on machine learning. This course covers the essentials of machine learning, including predictive analytics and working with decision trees. Explore several popular tree algorithms and learn how to use reverse engineering to identify specific variables. Demonstrations of using the IBM SPSS Modeler are included so you can understand how decisions trees work. This course is designed to give you a solid foundation on which to build more advanced data science skills.

Topics include: • Using the SPSS Modeler • Building a CHAID model • Adding a second model with C&RT • Analysis notes • Using a lift and gains chart • Exploring algorithms • Building a tree interactively • The Bonferonni adjustment • Handling nominal, ordinal, and continuous variables • Examining the CHAID tree • The Gini coefficient • Weighing purity and balance • Understanding pruning • Examining the C&RT tree • Applying stopping rules • Using the Auto Classifier tuning trick

1h 16m • COURSE

If you're working towards an understanding of machine learning, it's important to know how to work with decision trees. In this course, explore advanced concepts and details of decision tree algorithms. Learn about the QUEST algorithm and how it handles nominal variables, ordinal and continuous variables, and missing data. Explore the C5.0 algorithm and review some of its key features such as global pruning and winnowing. Plus, dive into a few advanced topics that apply to all decision trees, such as boosting and bagging.

Topics include: • Understanding QUEST functions and applications • C5.0 concepts and practical applications • Understanding information gain • Random forests • Boosting and bagging • Costs and priors

57m 13s • COURSE

We're on the precipice of a radical and disruptive new way of conducting all manner of transactions over the Internet. While still in its infancy, blockchain technology demands attention. In this introductory-level course, learn what blockchain is and what it might mean to you. Jonathan Reichental—named one of the world's top 100 CIOs in 2017—dives into blockchain technology from a conceptual perspective. The course is primarily non-technical by design, intended for those working in business leadership positions, data science, and IT management.

Jonathan begins by describing some of the current challenges with the Internet, including existing risks and security problems such as identity management. Next, he describes how traditional online databases function, so that you have a basis for how the blockchain redesigns this function. He then describes how the blockchain becomes a potential solution for many of the existing limitations of online databases. Since the blockchain has its genesis in Bitcoin—the digital currency—he provides some background on that too. He also discusses how blockchain technology actually offers new capabilities beyond simply solving old problems. To wrap up the course, Jonathan shares steps you can take in your organization to understand the implications of the blockchain.

Topics include: • Risk and security challenges • Rethinking the traditional database • What is the blockchain? • What problems does the blockchain solve? • Transforming transactions • Examples of the blockchain in action • Obstacles to blockchain adoption • Risks to existing solutions and enterprises

1h 31m • COURSE

Blockchain is an exciting new technology that is redefining how we store, update, and move data. Learn about the blockchain and the implications of decentralized, encrypted data storage for business and society, in this course with Dr. Jonathan Reichental. He begins by explaining exactly how the blockchain works, including the concepts of cryptography, mining, distribution, and smart contracts. Next, he describes how the blockchain enables the most popular cryptocurrency, bitcoin. Learn how new bitcoin is generated, how it is transacted, and the requirements for participating as either an exchange, a trader, or a miner. The course also covers other popular technology manifestations of blockchain, such as Hyperledger and Ripple. Dr. Reichental then puts blockchain technology in context in several different industries, including energy and security, and helps learners understand how to think about the blockchain in ways that can be applied in any field.

Topics include: • Blockchain basics • Public and private keys • How blockchain enables bitcoin • Blockchain and the electrical grid • Blockchain and identity management • Risks of blockchain

38m 9s • COURSE

The Internet of Things (IoT) is more than just smart or connected devices. In this course, learn what IoT is, and how it works from a technical standpoint. Bruce Sinclair provides a broad overview of IoT, explaining each of its main components. He also goes into the software-defined product—the digital twin of the physical product—as well as the hardware-defined product, explaining how sensors and embedded systems help to gather data. Plus, he dives into the network fabric, and explains what external systems are and why it's important to consider them when designing an IoT product.

Topics include: • IoT value modeling • The software-defined product • The hardware-defined product • Embedded systems • Connected sensors • The network fabric • OT IT and fog networks • Analytics and big data • Data services

1h 32m • COURSE

The continuous development of IoT ecosystems promises a future in which our homes, cars, and cities are more connected. But as this technology evolves, it has become increasingly important to tackle the communication and compatibility challenges facing the billions of connected devices already out in the world. In this course, learn about IoT standards and ecosystems. Instructor Zahraa Khalil provides a high-level look at the IoT ecosystem, discussing IoT markets, technology, and standards. She also goes over the challenges facing the development of IoT—including security, privacy, and legal issues—the IoT standards development process, and IoT protocols for device management. Plus, she shares examples of IoT ecosystems in action by exploring case studies of smart cities.

Topics include: • IoT architecture models and components • IoT ecosystem • IoT technology, markets, and standards • IoT technology • Security, privacy, and legal issues • IoT device management • IoT protocols for device management • IoT device management challenges and applications Smart cities

2h 31m • COURSE

Building and operating an information security program at your organization can be challenging. The scope can be vast and complex. Thinking of all the ways an organization can fail and coming up with actionable measures you can take to prevent issues, mitigate risk, or recover from events is a large undertaking. In this course, Kip Boyle, president of Cyber Risk Opportunities, guides you through the entire process of creating an information security program, rolling it out to your organization, and maintaining it for continuous risk management.

Topics include: • Goals and components of an information security program • Measuring and managing information risks • Reducing risks to an acceptable level • Using a workflow to organize your work • Communicating progress with executives and stakeholders • Demonstrating compliance