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2. A self-taught engineer at Google shares the 8 best Google ...

   www.aol.com/self-taught-engineer-google-shares...

   Gaba is a self-taught engineer who used Google's free and auditable courses when learning to code. Gaba says there's a course for programmers at every level on topics like Python and generative AI.

3. Google Digital Garage - Wikipedia

   en.wikipedia.org/wiki/Google_Digital_Garage

   Google Digital Garage is a nonprofit program designed to help people improve their digital skills. [1] It offers free training, courses and certifications [ 2 ] [ 3 ] via an online learning platform .

4. Andrew Ng - Wikipedia

   en.wikipedia.org/wiki/Andrew_Ng

   His machine learning course CS229 at Stanford is the most popular course offered on campus with over 1,000 students enrolling some years. [23] [24] As of 2020, three of most popular courses on Coursera are Ng's: Machine Learning (#1), AI for Everyone (#5), Neural Networks and Deep Learning (#6). [25]

5. Coursera - Wikipedia

   en.wikipedia.org/wiki/Coursera

   The free courses (also called "auditing a course") do not include a certificate of completion or grades or any other instructor feedback. A free course can be "upgraded" to the paid version of a course, which includes instructor's feedback and grades for the submitted assignments, and (if the student gets a passing grade) a certificate of ...

6. Google AI - Wikipedia

   en.wikipedia.org/wiki/Google_AI

   Google collects its AI initiatives under Google.ai. Archived October 8, 2018, at the Wayback Machine. Google collects AI-based services across the company into Google.ai – "Google.ai is a collection of products and teams across Alphabet with a focus on AI." Google's deep focus on AI is paying off. Archived October 20, 2020, at the Wayback ...

7. fast.ai - Wikipedia

   en.wikipedia.org/wiki/Fast.ai

   In 2018, students of fast.ai participated in the Stanford’s DAWNBench challenge alongside big tech companies such as Google and Intel.While Google could obtain an edge in some challenges due to its highly specialized TPU chips, the CIFAR-10 challenge was won by the fast.ai students, programming the fastest and cheapest algorithms.