Here you can find the subject matter and assigned reading for every class day as well as expected homework dates.
Please check back here frequently as the schedule is subject to change.
Class number | Date (2025) | Topic | Notes |
|---|---|---|---|
1 | W 8/27 | Lecture 0: Course overview; syllabus | |
n/a | M 9/1 | NO CLASS. (Labor Day) | |
2 | W 9/3 | Lab 0: Python basics I; Jupyter and colab | HW00 assigned; due 2025-09-10) |
3 | M 9/8 | Lecture 1: Numeracy and data cleaning | |
4 | W 9/10 | Lab 1: Python basics II | HW01 assigned; due 2025-09-28) |
5 | M 9/15 | Lecture 2: Descriptive Statistics | |
n/a | W 9/17 | NO CLASS (Prof. traveling) | |
n/a | M 9/22 | NO CLASS (Rosh Hashana) | |
n/a | W 9/24 | NO CLASS (Rosh Hashana) | |
6 | M 9/29 | Lab 2: plotting (matplotlib) | HW02 assigned; due 2025-10-07) |
n/a | W 10/1 | NO CLASS (Yom Kippur) | |
7 | M 10/6 | Lecture 3: Probability theory | |
8 | W 10/8 | Lab 3: computing empiricial PDFs and CDFs (numpy, scipy) | HW03 assigned; due 2025-10-14) |
n/a | M 10/13 | NO CLASS (Columbus Day) | |
9 | T 10/14 (note abnormal day of week) | Lecture 4: Probability distributions (including for extreme values) | |
10 | W 10/15 | Lab 4: fitting probability distribution to data, including for extreme values (scipy) | HW04 assigned; due 2025-10-22) |
n/a | M 10/20 | NO CLASS (CCNY closed) | |
11 | W 10/22 | Special Lab: generative AI tools | |
12 | F 10/24 (note abnormal day of week) | MIDTERM 1 | |
13 | M 10/27 | Lecture 5: Linear regression | |
14 | W 10/29 | Lab 5: linear regression (pandas) | HW05 assigned; due 2025-11-05) |
15 | M 11/3 | Lecture 6: Hypothesis tests | |
16 | W 11/5 | Lab 6: t-tests | |
17 | M 11/10 | Lecture 7: Timeseries analysis | |
18 | W 11/12 | Lab 7: timeseries analysis | |
19 | M 11/17 | Lecture 8: spectral analysis | |
20 | W 11/19 | Lab 8: spectral analysis | |
21 | M 11/24 | MIDTERM 2 | |
n/a | W 11/26 | NO CLASS (Happy early Thanksgiving!) | |
22 | M 12/1 | Lecture 9: Neural networks | |
23 | W 12/3 | Lab 9: neural networks (pytorch) | |
24 | M 12/8 | Lecture 10: Other machine learning methods | |
25 | W 12/10 | Lab 10: final project work time | |
26 | M 12/15 | Final project presentations |