Education, Technology, Data Science, Artificial Intelligence

Learn AI, Cognitive, Data Science, Programming, & Cloud Computing from Free Online Sources

Free online technology education courses

Introduction

In this post, I introduce free learning programs by industry experts and industry skill badges offered by the Cognitive Class AI to help you boost your data science, machine learning, cognitive computing, cloud computing, deep learning, Blockchain, programming, open-source tools, and artificial intelligence capabilities online at your convenience.

Continuous learning and applying our knowledge can be powerful and critical success factors for achieving our professional goals.

The Cognitive Class AI offers a wide variety of professional learning paths, as free of charge, to learners globally. In this article, I provide you with some prominent learning path samples with links so that you commence achieving your 2020 professional education and career development goals.

I will also provide you with a list of sample industry badges that you can earn by undertaking these online training courses.

The badges can help you promote your knowledge, skills, experience, and expertise globally hosted in a centralized industry-recognized digital program governance organization such as Credly’s Acclaim, which is the world’s largest network of individuals and organizations using verified achievements to unlock opportunities.

You can join millions of professionals in sharing your achievements online with a simple link. I cover the details of the Acclaim digital badge program in a separate post.

Let’s start with reviewing some sample learning paths in the Cognitive Class AI that you can undertake for free.

Links to Free Online Courses

Deep Learning

Through guided lectures and labs, you’ll first learn Neural Networks, and an overview of Deep Learning, then get hands-on experience using TensorFlow library to apply deep learning on different data types to solve real-world problems.

In this learning path, you will be able to learn the basic concepts of Deep Learning and TensorFlow. Then, you will get hands-on experience in solving problems using Deep Learning. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions.

This concept is then explored in the Deep Learning world. You will learn how to apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained. Finally, the course covers different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks and Autoencoders.

Data Science for Business

If a trend is identified using big data, how can it be applied to solving complex day-to-day problems? Are there implications of using this data? This learning path addresses the principles of data science to explore data privacy, regression analysis, text analytics, data visualization and predictive modelling to promote topical awareness.

Second-guessing your decisions is not an option when the stakes are high. Every day, we as humans, make tonnes of decisions, from the point that the alarm rings in the morning, to the location of our pillows at the end of the night. Some decisions have lasting impacts, while others move us from place A to place B. How we make these decisions and the rationale driving these decisions are critical to our success.

This learning path is designed to demonstrate how to identify insights from data to support consistently making clear and rational decisions. Courses in this learning path are case-study driven, and put data manipulation, data visualization and analytical techniques in the context of every day to put an end to the second guess.

Blockchain for Developers

Take this series of courses to go from blockchain basics to developing IoT supply chain applications for blockchain business networks. The first course covers basic blockchain concepts such as shared ledgers, smart contracts, provenance, and consensus.

You’ll also see what makes a good blockchain network use case and finally build a simple blockchain network. The second course shows you how to create more complex blockchain applications. You’ll also learn what developers need to know to contribute to the overall blockchain solution for a business network.

The last course shows you how to build a blockchain network for a specific use case: tracking food and other perishable goods through a supply chain. You’ll use an IoT asset tracker and Node-RED to track and collect temperature, motion, and other data. That data is fed to a blockchain network to be used as an immutable record of transaction history throughout the journey of the cargo.

Data Science Foundations

Dust off your lab-coat and stretch out your fingers and get ready for the journey of a lifetime that will have you see every day through a new lens. Looking at mundane events becomes interesting from the speed of your windshield wipers wiping off the rain to the rate of plant growth in ditches along highways under different conditions.

As the study that leads into all things pertinent to humans in the present, this path is a must for all who have even the slightest interest in this field.

This learning path currently consists of one course that introduces you to Data Science from a practitioner point of view, to courses that discuss topics such as data compilation, preparation and modelling throughout the life-cycle of data science from basic concepts and methodologies to advanced algorithms. It also discusses how to get some practical knowledge with open source tools.

Scala Programming for Data Science

To light a fire, do you use a match, a lighter, or a torch? Depends on the size of the fire, much like the decisions that lead one to use Python, R, or Scala. Spark your interest in selecting the tools you need to tackle Big Data with ease, that will not just blow out.

Data Scientists tend to favour one of three programming languages, Python, R, or Scala. Which to choose? Learn Scala if you are an aspiring or a seasoned Data Scientist (or Data Engineer) who is planning to work with Apache Spark to tackle Big Data with ease.

This learning path has been developed by Lightbend (formerly Typesafe), the undisputed authority on all things Scala.

Big Data Fundamentals

Are you interested in understanding ‘Big Data’ beyond the terms used in headlines? Then select this learning path as an introduction to tools like Apache Hadoop and Apache Spark Frameworks, which enable data to be analyzed on mass, and start the journey towards your headline discovery.

Data is comprised of bits and bytes, and as humans we are immersed in data in our every-day lives. The value that data holds can only be understood when we can start to identify patterns and trends within the data that then trigger questions to better understand the impact of our actions.

This learning path is designed to move participants from an initial understanding of Big Data terms and concepts to working with toolsets to dig into the data itself and start identifying the patterns and trends that would otherwise go unnoticed.

Spark Fundamentals

Solid understanding and experience, with core tools, in any field promotes excellence and innovation. Apache Spark, as a general engine for large scale data processing, is such a tool within the big data realm.

This learning path addresses the fundamentals of this program’s design and its application in the everyday. Ever waited overnight to run a report and to come back to your computer in the morning to find it still running.

When the heat is on and you have a deadline, something is not working. With larger and larger data sets you need to be fluent in the right tools to be able to make your commitments. This learning path is your opportunity to learn from industry leaders about Spark. This path provides hands-on opportunities and projects to build your confidence within this toolset.

Hadoop Fundamentals

Are you interested in moving beyond the elephant in the room and understanding Hadoop as a foundational toolset in your future?

Then select this learning path to gain exposure to the tools used in Big Data, Hadoop’s core components and supporting open source projects. Hadoop is a name that represents two items, one a child’s toy and the other an open-source framework for distributed storage and processing of big data.

In both contexts, interaction with Hadoop is foundational in personal growth and development. This learning path covers content that is critical to your success in this realm. It takes you on a journey that explains the Hadoop conceptual design, then it looks at how to use the application and then manipulate data without the use of complex coding.

Applied Data Science with Python

Learn how to code in Python for data science, then analyze and visualize data with Python with packages like scikit-learn, matplotlib and bokeh. This is an action-packed learning path for data science enthusiasts and aspiring data scientists who want to learn data science hands-on with Python.

In these data science courses, you’ll learn how to use the Python language to clean, analyze and visualize data. Through our guided lectures and labs, you’ll get hands-on experience tackling interesting data problems. This is an action-packed learning path for data science enthusiasts who want to work with real-world problems using Python.

Make sure to take this learning path to solidify your data skills in Python, before diving into machine learning, big data and deep learning in Python.

Containers, microservices, Kubernetes, and Istio on the Cloud

After completing this learning path, you’ll understand 12-factor apps and how microservices are managed with the IBM Cloud Kubernetes Service and Istio. You’ll get hands-on experience working with containers, Kubernetes, and how to deploy containerized apps.

You’ll learn how to deploy microservices in a cluster and how to connect, manage, and secure those microservices. Get hands-on experience with Kubernetes container orchestration. Learn how Kubernetes and IBM Cloud Kubernetes Service help you more easily deploy and scale containers and applications.

Discover how microservices and Istio pair together for cloud-native apps. Learn how Istio and IBM Cloud Kubernetes Service help you securely and seamlessly deploy containers and apps. Start managing your microservices with Istio on IBM Cloud Kubernetes Service. This course shows you how to better control traffic to services, observe service health, and secure the service mesh.

Lightbend Reactive Architecture: Foundations

Designing cloud-native systems and microservices requires architects and teams to think differently. The Lightbend Reactive Architecture learning path teaches development managers, architects, and software developers — how to think about Reactive Systems from design through to production. Cloud-native systems need to be responsive.

Designing these systems requires architects to think differently, in order to build software that can be both resilient and elastic. These Reactive Systems are built on a message-driven foundation.

As microservices have emerged as the gold standard of developing modern software applications, every team needs to develop a deep understanding of how to design, build, and operate software in a Reactive world if they want to remain relevant.

The Lightbend Reactive Architecture learning path teaches teams how to leverage the Reactive Principles to build software that will carry them into the future.

Lightbend Reactive Architecture: Advanced

Distributed systems built on Reactive Microservices introduce new challenges and require new tools to meet those challenges. The Lightbend Reactive Architecture: Advanced learning path teaches managers, developers, and architects new techniques to help cope with the realities of distributed architectures.

You will learn how the Lightbend Reactive Platform can be used to build the distributed systems of tomorrow. Cloud-native systems are commonly built using Reactive Microservices. In the Lightbend Reactive Architecture: Foundations learning path, we discovered what makes a system Reactive. Now, in the Lightbend Reactive Architecture: Advanced learning path we will take that a step further.

We will learn about some of the problems that are introduced when we start building distributed systems, and solutions that can help us overcome those problems. We will learn about the impact of the CAP theorem, and the laws of scalability. We will explore new patterns such as sharding, conflict-free replicated data types (CRDTs), sagas, and command query responsibility segregation (CQRS). These new ideas will help us build the next generation of systems that will allow us to scale beyond what we previously thought possible.

Hadoop Administration

So how do you control an elephant? In this context, with your mouse and a bit of patience, you can install, configure and administer a Hadoop cluster. Be the envy of Zookeepers, and contribute to open-source projects such as Sqoop, Flume, Oozie, and more!

A zookeeper must keep the animals in check from the start to the end. As an administrator of infrastructures, you will too. This learning path is designed to keep you ahead of the game, providing the skills you need to interact, manipulate and troubleshoot, all the while keeping your cool.

Hadoop Data Access

So you know how to drive (code in SQL) and now you have the keys to your first car (the link to the data set). Ready to drive? Consider this course as the test drive to accessing data in big data systems using Hive, SQL, and HBase. Just don’t get stung!

So what are the similarities between a beehive and an Apache hive? Efficiency, ingenious architecture and the constant draw to find its sweet rewards are just some. If SQL is the equivalent of the bee-keeper’s smoke, this course demonstrates how to use the SQL to access Hadoop data. It speaks to Big SQL, HBase system, and architecture for real-time access. Suit up and realize the buzz!

Data Management with IBM

Learn how to store, manipulate, and access your data with IBM’s data management tools! This is an action-packed learning path is for data enthusiasts who want practical skills in managing and analyzing data in databases. In this learning path, our guided lectures and labs will help you get hands-on experience with data management using IBM offerings.

You will get started by learning about SQL and relational database fundamentals. Then get to know about NoSQL and Databases as a Service. Acquire more in-depth relational database skills with the IBM flagship offering DB2 and the next-generation cloud-based dashDB.

And finally learn how to analyze ad visualize data in relational databases using the powerful R programming language. This is an action-packed learning path is for database enthusiasts, data engineers and database developers who want a solid foundation of real-world skills in data management.

Cognitive Analytics with IBM

Learn how to analyze data with IBM’s cognitive tools! Today, cognitive data analytics is a must-have feature for most applications that we use every day, such as predicting the weather, recommender systems in shopping apps, and fraud detection in credit card tools.

If you are interested in learning how data analytics actually works and how it augments human ability, then this learning path is for you. Cognitive analytics is all about unlocking hidden insights from your data. Data can be structured, unstructured, audio, or visual — and to make all that data work together as an engine that augments human ability.

In this learning path, you will learn how to use state-of-the-art analytic tools from IBM to accelerate your business. You will learn how to use statistical concepts to describe, explore, and understand your data. You will also go through modeling approaches from basic machine learning concepts to advanced algorithms and optimizations.

Get some practical knowledge with open source Machine Learning libraries like Apache SystemML, and learn how to use the most popular language by data scientists for machine learning: Python. In the end, learn how to use Watson Analytics, a smart and fast service that uses the power of IBM’s Watson to automatically discover insights in your data.

Applied Data Science with R

Through our guided lectures and labs, you’ll get hands-on experience tackling interesting data problems. This is an action-packed learning path for data science enthusiasts who want to learn about data analysis, accessing databases with R, and visualization. In these data science courses, you’ll learn how to use the R language to access databases, and clean, analyze, and visualize data with R. Through our guided lectures and labs, you’ll get hands-on experience tackling interesting data problems. This is an action-packed learning path for data science enthusiasts who want to work with real-world problems using R.

Industry Badges offered by Cognitive Class AI

The Cognitive Class also offers industry-recognized digital badges, which you can demonstrate in your Acclaim profile to current employees, prospective recruiters, and your peers.

There are many badges to help you demonstrate your knowledge, skills, experience, and expertise in Data Science, Artificial Intelligence, Cognitive Computing, Programming, Cloud, and more…

You can access the badge program from this link.

How is Cognitive Class helping the United Nations' goals?

The first concrete step to help with the UN goals is by sponsoring the development of a Data Science course for High Schools. In partnership with Fireside Analytics, Blyth Academy, and Virtual High School (Goal 17), we are democratizing access to Data Science education by delivering quality content (Goal 4).

Access to this kind of education will reduce inequalities (Goal 10), and will eventually provide the pipeline of the skilled individual in data science that is so much needed to propel economic growth and jobs (Goal 8). The world’s collaborative to-do list for the next 15 years.

The global goals address social, economic, environmental, and climate challenges in a comprehensive, integrated way. The goals are about more than words: they are about concrete action. By together tackling global goals, we can be the first generation to end extreme poverty, the most determined generation to fight inequality, and the last generation to address climate change.

Conclusions

I compiled these useful learning programs as a giveback to the Medium community members who strive to learn and improve their skills relentlessly.

I hope you find this post useful, as it covers an actionable information pack to get you started with your learning journey to speed up your development goals.

Let’s remember continuous learning and applying our valuable knowledge can be powerful and critical success factors for developing new skills, gaining new experiences, enhancing our expertise, and achieving our professional goals.

In addition, to help my readers, I compiled helpful online resources and videos to jumpstart learning about quantum computing. For example, you can install a quantum software development kit, write quantum code, and execute your code using a quantum computer for free.

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