## Fall 2022

- August 22
- Lecture 1 video, Jupyter notebook, and LIVE exercises.
- History of the course. Arithmetic operations in Python. Introduction to functions and scalar data types. Syllabus for this semester.
- August 24
- Lecture 2 video, Jupyter notebook, and LIVE exercises. PS01 posted, due 9/2/22.
- Indentation. If-Then logic. Comparison operators. Branching programs. Looping programs: while, for, and range.
- August 29
- Lecture 3 video, Jupyter notebook, and LIVE exercises.
- Linear search versus bisection search. How to use this to compute square roots. Review of functions and NoneType.
- August 31
- Lecture 4 video, Jupyter notebook, and LIVE exercises.
- Default values for functions. Docstrings. Abstraction. Recursion.
- September 7
- Lecture 5 video, Jupyter notebook, and LIVE exercises (v2).
- Python Tutor. Iterative versus Recursive Implementations. Methods on Strings. The Subset-Sum problem.
- September 12
- Lecture 6 video, Jupyter notebook, and LIVE exercises.
- Collection Data Types---lists, tuples, sets, and dictionaries---and the Edit Distance on Strings.
- September 14
- Lecture 7 video, Jupyter notebook, and LIVE exercises.
- "One Liners" such as list comprehension and lambda functions. Brief introduction to Object Oriented Programming (OOP).
- September 19
- Lecture 8 video, Jupyter notebook, and LIVE exercises.
- More Object Oriented Programming (OOP) and Intro to Data Structures.
- September 21
- MIDTERM 1 IN-CLASS EXAM. Here is a study guide.
- Covers the first 6 lectures plus list comprehension!
- September 26
- Lecture 9 video, Jupyter notebook, and LIVE exercises.
- OOP for Mortgages and Plotting.
- September 28
- Lecture 10 video, Jupyter notebook, and LIVE exercises.
- Numpy array operations. Simulating random phenomena.
- October 3
- Lecture 11 video, Jupyter notebook, and LIVE exercises.
- Randomness vs. Determinism. Frequency stats. Basic Distributions.
- October 5
- Lecture 12 video, Jupyter notebook, and LIVE exercises.
- Basic Hypothesis Testing: signficance levels, 1 and 2 tail tests.
- October 12
- Lecture 13 video, Jupyter notebook, and LIVE exercises.
- Intro to Machine Learning via Regression. The Train-Model-Predict Paradigm

*Nota Bene: Registered students must submit HW via the servers.*