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Understand The Fundamentals of AI Through This Deep Learning and Data Analysis Training

Artificial Intelligence and deep learning are thriving parts of the IT industry. This bundle shows you how to master them.

Artificial intelligence and deep learning are drawing patterns out of the seeming noise in big data, and it’s changing our world in broad and subtle ways: Finding practical uses for holograms, developing new tools for first responders, and even writing our creepy campfire stories for us. AI and deep learning are becoming an indispensable skill for IT professionals, academics, and anyone who handles large data sets or needs to use heavy processing power to solve problems.

The Deep Learning & Data Analysis Certification Bundle, currently at 97% off, has all the tools you need to begin teaching computers how to dig into datasets, whether you’re completely new to the field or looking to sharpen your skills.

Google Data Studio

If you’re completely new to AI and deep learning, “Business Data Visualization, Analytics & Reporting with Google Data Studio” lays out how to use Google’s free tool for taking large amounts of data and turning it into easy-to-read visualizations, from simple charts and graphs to more complex designs. You’ll learn how computers handle these tasks, how to think about data visually and ground yourself in the basics of statistics.

Python

If you’ve got a background in Python and general computer science, you can leverage it to begin deep learning work right away.

“Image Processing & Analysis Bootcamp with OpenCV and Deep Learning in Python” gets you started by looking at a common task for Python; sorting, classifying, and analyzing large databases of images. Instagram is built on Python for a reason, after all.

“Keras Bootcamp For Deep Learning & AI in Python” goes through Keras, one of the most popular deep learning Python frameworks. Keras was built by Google to perform the hard data science work that drives the company, and it’s served as the basis for countless deep learning projects since.

“Master PyTorch For Artificial Neural Networks (ANN) & Deep Learning” wraps up the Python end of things with PyTorch, developed by Facebook’s AI research team. PyTorch pairs the Torch open-source machine learning library with the Python interface, easing you into the more complex aspects of building and guiding neural networks.

It’ll also set the stage for the real powerhouse in deep learning and AI, the R language.

R

The R programming language is the gold standard in statistical computing and visualization, built from the ground up to tackle vast repositories of information and make sense of them. “Statistics & Machine Learning For Regression Modelling With R” will show you how R models statistical analysis through regressions, one of the core tools of all deep learning programs. “Data Analysis Masterclass With Statistics & Machine Learning In R” will then broaden it out to more statistical tools so you can get a full sense of how R handles data and the breadth of what you can do with it.

“Complete Artificial Neural Networks & Deep Learning In R” will then show you how to automate these statistical tools and create the deep learning you need, looking at how several data science packages work via R and discussing the underlying concepts. “Harness the Power of the H2O Framework For Machine Learning in R” will look at H20 and how it functions, setting the stage for you to probe the patterns hidden in data on your own.

As the amount of data we collect and work with expands, managing it will be one of the fundamental day-to-day challenges of any career. For $39.99, the Deep Learning & Data Analysis Certification Bundle will help you stay on top of a changing industry, and pull back the curtain on how data is being used to change the world.

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 Futurism.com editorial staff.

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