There are a lot of new technologies coming out at an ever increasing pace.

How do you keep up?

Enter Microsoft Learn: the easiest way to learn products and services through task-based, interactive learning.

With hundreds of free courses, localized into 23 different languages, covering Azure, Dynamics, Power Apps, Flow, with more coming.

Whether you’re just starting or an experienced professional, our hands-on approach helps you arrive at your goals faster, with more confidence and at your own pace.

The workforce of the future will require to have a different set of skills or even skills that the schools of today provide.

Realistically, this means on the job training and upskilling of employees.

For instance, employees need to know how to use wearables in their daily job, how to provide effective instructions to robots and “cobots,” and how to repair a motor without formal training.

The workforce of the future learns in a different way to the workforce of the past. As a first step, businesses need to define the exact skillset needed for their very own factory of the future. Then, dedicated courses and materials (mockups, case studies, projects) need to be defined and developed.

If you’re a frequent reader of this blog or Data Driven listener, then you know that I am a fan of lifelong learning. This has helped me immensely in my career (and life in general).

This curated collection of online ML and Data Science courses comes courtesy of Delta Analytics, author and trainer Aurélien Geron, University of Wisconsin–Madison, AI researcher Goku Mohandas, University of Waterloo, National University of Singapore, and ETH Zurich.

If, after reading this list, you find yourself wanting more free quality, curated learning materials, check out the related posts at the bottom. Happy learning!

If you’re curious about getting into Data Science, then here’s a great free resource: Edureka video on Data Science. You can watch an end to end, detailed and comprehensive knowledge dump on Data Science.

This Data Science video will start with basics of Statistics and Probability and then move to Machine Learning and Finally end the journey with Deep Learning and AI.

When I started to pivot my career towards data science, there was not a well-worn path from app developer to data scientist. In fact, I encountered more than a few naysayers when I started.

Now in 2019, there are multiple paths forward. Many require significant financial investment, but not all do. All require a fair bit of time commitment.  Here’s a great compiled list of free resources.