Schedule for Data Science curriculum construction

Week 1-4 Python
Week 5 - Intro to Data Science
- What is DS?
  - Theory of DS (collection and aggregation of data, analyze and display results)
- Statistics
  - Population vs Samples
  - Measures - EV/Variance/stddev
- Linear Algebra
  - Vectors/matricies and dot/cross product
  - Representing m n-dimensional samples
- Data santization
  - Data importing
  - Data cleaning
  - Data formatting
Week 6 - Intro to Machine Learning
- What is ML?
  - Formal definition of ML involving learner L, samples S, with error E
Week 7 - Machine Learning Algorithms
Week 8 - Intro to Linear Algebra/Calculus
Week 9 - Intro to Deep Learning
Week 10 - Deep Learning Algorithms
Week 11 - ???
Week 12 - Putting it all together
Week 13-14 - Project

Provide feedback