Daily Schedule (Actual — Kept Retrospectively)

Part 1: Scientific Python (using Imad Pasha)

• Regular meeting times are Wednesdays and Saturdays (at 11)

Week 1 (May 16 and 17):

• May 16: Self study chapter 1 through chapter 3 and review with Brian
• May 17: Complete Ch. 4: Introduction to Python — Problem Set 1: Use for loops to compute the first 20 Fibonacci numbers

Week 2 (May 21 & 24):

• May 21: Study Ch. 5: Visualization with Matplotlib — Learn to use jupyter-lab — Make some histogram and scatter plots using the iris dataset

FROM HERE DOWN IS PLAN NOT ACTUAL

• Ch. 6: Numerical Computing with NumPy

Week 3 (May 27 & 30):

• Ch. 7: Scientific Computing with SciPy
• Ch. 8: Astropy and Astronomical Packages

Part 2: Data Science Foundations (using Joel Grus)

Week 4 (June 3 & 6):

• Ch. 1–2: What is Data Science? Python Review
• Ch. 3: Visualizing Data

Week 5 (June 10 & 13):

• Ch. 4–6: Linear Algebra, Statistics, Probability

Week 6 (June 17 & 18):

• Ch. 7–8: Hypothesis Testing, Gradient Descent

Week 7 (June 24):

• Ch. 9–10: Getting Data, Working with Data
• (Optional bonus topic of Ch. 11–12: Machine Learning intro)