100 Days of AI
A 100-day self-study challenge that links one AI or machine-learning concept per day to a companion blog post, moving from machine-learning foundations through neural-network training to AI agents in production.
100 Days of AI is a structured reading plan rather than original course content: each day names a topic, such as supervised versus unsupervised learning, loss functions, regularization or recurrent neural networks, and links to a blog post that explains it. Learners are asked to spend 30 to 60 minutes a day, write a short note in their own words, and use built-in revision days to review earlier material instead of reading something new.
The challenge is organized into phases, starting with machine-learning foundations and continuing into how neural networks learn, with later phases extending into AI agents used in production. It is maintained by the founder of Outcome School and is released under the Apache-2.0 license.