The material in this repo is designed for the idiomatic teaching method. It differs from the traditional A-Z methodology. In A-Z, education/training material is split into a set of tasks (A, B, C...) and then sequenced into a progression (start at A and end at Z).
The vast proponderance of education/training material available (and its quite vast) for machine learning and artificial intelligence is of the A-Z method. At Google Developer Relations, we have heard from software developers that it's not working. They say they can go through the material, complete exercises, pass quizzes, etc -- yet it still doesn't click. Personally, as an educator, I have heard this frequently.
In Idiomatic teaching, one teaches patterns, and how those patterns are connected. Many will feel instead of starting at the beginning and doing a vertical progression, one starts in the middle and then spirals around -- always teaching patterns and how they connect. What I have personal found switching from A-Z to Idiomatic teaching of machine learning in 2018, were my students telling me now I get it --thank you. It's a style of teaching that appears to work universally.
- It's inclusive - eliminate all gender specific phrasing, and replace with us, we and one.
- It's welcoming - frequent use of the word let's, where students feel let's learn together.
- It's lifelong learning - instructor present themselves not as a master, but master/student -- while having mastered the subject, the instructor continues to learn from the students.
- It's exploring - eliminate pushing to correct answers, and replace with exercises that push the learner to explore.
- It's bias free - eliminate rewards for excellence, make learning non-judgemental, reward intiative, and intuition.
- It's intuitive - connecting with patterns and examples.
The education is inclusive where no software developer feels they will be left behind.