Master AI with This Bundle of Python Coding Courses

Learn how to build the machines of the future with this 97% off Python bundle

Artificial intelligence and machine learning are making our lives easier — in some obvious ways, and some surprising ones. It’s helping historians understand ancient languages we’ve been unable to crack, personalizing our workouts, and even writing convincing op-eds. Yet despite being everywhere, the field can feel opaque even to programmers.

The Ultimate Python & Artificial Intelligence Bundle, which is currently $39.99 or 97% off the usual price, aims to make the design, building, and deployment of these tools transparent. Whether you’re looking to build a better fitness regimen or advance your IT career, you’ll find what you need in the 35 hours of training in this bundle.

The Basics

Completely new to Python? This bundle starts with two courses to show you how it functions. Start with Python for Beginners: Learn All the Basics of Python and Python For Beginners: The Basics For Python Development to learn why this powerful, flexible programming language is one of the fundamentals of not just AI, but your favorite apps, websites, and more. Once you have that grounding, you can move on to Python: Introduction to Data Science & Machine Learning A-Z. Much of machine learning and AI is about the management and analysis of large data sets, and applying data science can yield some fascinating results.


If data science intrigues you, you’ll want to follow up with H20. H2O is a scalable and automated system that does the grunt work of data science while the programmer refines the more complicated details in the back-end. Artificial Intelligence (AI) in Python: An H2O Approach shows you how this works in practical terms, whether you’re looking to use it for academic work or in the private sector.


Keras, an open-source library of AI tools that uses the Python interface, is one of the most commonly used tools for machine learning, not least because it was developed and is utilized by Google. It’s designed to be deployed on multiple platforms and can even learn through distributed networks. As such, anybody looking to work with AI will need to have an understanding of how it works.

Image Processing & Analysis Bootcamp with OpenCV and Deep Learning in Python starts with a common Keras task: sorting through the billions of photos that flood websites and social media networks every day looking for common data. If you’ve ever wondered how a social media network can guess your face out of a crowd, this will show you how that works. Next, Keras Bootcamp for Deep Learning & AI in Python will expand on those skillsets to show you how Keras uses both common and uncommon data to build and operate neural networks.


PyTorch is the software that drives deep learning, including Tesla’s self-driving technology and Uber’s probabilistic estimating tool, Pyro. Master PyTorch for Artificial Neural Networks (ANN) & Deep Learning will explain what makes it stand out for these types of applications and how to use it for deep learning functions.


Finally, for the complicated statistical computing and design demanded by heavy industry, you’ll learn to use the R programming language, built for handling statistics and data mining. Practical Data Pre-Processing & Visualization Training with R and Pre-Process & Visualize Data with Tidy Techniques in R will show you the two most popular R functions, how it can wrangle data to make it more manageable for humans, and how it can visualize that data in effective terms to see patterns and make more informed decisions.

It’s important to remember AI and machine learning are tools for humans to benefit from, not replacements for humans. For just $39.99, the Ultimate Python & Artificial Intelligence Certification Bundle will put you on the road to mastering these tools—and furthering your career.

Futurism fans: To create this content, a non-editorial team worked with an affiliate partner. We may collect a small commission on items purchased through this page. This post does not necessarily reflect the views or the endorsement of the editorial staff.

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