Google offers free crash course on machine learning

Anyone interested in machine learning can take Google’s Machine Learning Crash Course (MLCC) – for free.

Initially created for Google engineers, the 15-hour crash course, revealed this morning on the Google Developers Blog, covers machine learning fundamentals, such as loss and gradient descent, classification models and neural nets. The course will include videos from Google machine learning experts, in addition to short text lessons. Participants will also be able to play with “educational gadgets” alongside instructional designers and engineers.

Each MLCC lesson will finish with a real-world example of machine learning systems.

“MLCC also contains sections enabling you to learn from the mistakes that our experts have made,” says Google, adding machine learning is “so vast that every technical person should learn machine learning fundamentals.”

Worried about a lack of a math skills? That’s okay, says Google. While understanding some calculus, algebra and a little elementary statistics is helpful, it’s not a requirement. Neither is programming. A small percentage of MLCC courses include Python programming exercises, but Google says non-programmers can skip them.

“Many of the Google engineers who took MLCC didn’t know any Python but still completed the exercises,” the blog post read. “Instead of writing code from scratch, you’ll primarily manipulate the values of existing variables. That said, the code will be easier to understand if you can program in Python.”

MLCC relies a lot on various forms of media and hands-on interactive tools to build the fundamental machine learning concepts.

“You need a technical mind, but you don’t need programming skills,” says Google, adding kicking off a Kaggle competition to help DonorsChoose.org, an organization that helps public school teachers across the country to request materials and experiences they need to help their students grow.

More than 500,000 proposals are expected in 2018.

The course, accessible worldwide, will be available in English, Spanish, Korean, Mandarin, and French.

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Jim Love, Chief Content Officer, IT World Canada

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Alex Coop
Alex Coophttp://www.itwc.ca
Former Editorial Director for IT World Canada and its sister publications.

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