Schedule of Events
Class meetings are held on Mondays, Tuesdays, and Thursdays.
On Mondays, workshops are 3:00 - 3:50pm in Forest Resources, Room 0304.
On Tuesdays and Thursdays, lectures are 2:20 - 3:35pm in Chemistry, Room 0674.
| Date | Topic | Links | |
| Thurs, 8/17 | Lecture 1: Course Introduction and Review | pptx | pdf | |
| Thurs, 8/17 | Homework 1 Released | pdf | handout | |
| Mon, 8/21 | Workshop 0: Setting up your Python Environment | materials | video | |
| Tues, 8/22 | Lecture 2: Python and Machine Learning Crash Course | (see Lecture 3) | |
| Thurs, 8/24 | Lecture 3: Python and Machine Learning Crash Course | ipynb | html | |
| Mon, 8/28 | Workshop 1: Overview of PyTorch | materials | |
| Tues, 8/29 | Lecture 4: Linear Algebra Review | mybinder | uga bhub | github | |
| Thurs, 8/31 | Workshop 2: Canceled | ||
| Mon, 9/4 | No Class - Labor Day | ||
| Tues, 9/5 | Workshop 3: Julia | materials | |
| Thurs, 9/7 | Lecture 5: Dense Motion Analysis | pptx | pdf | |
| Thurs, 9/7 | Homework 1 Due ; Homework 2 Released | pdf | handout | |
| Mon, 9/11 | Workshop 4: Support Vector Machines | materials | |
| Tues, 9/12 | Lecture 6: Linear Dynamical Systems | pptx | pdf | |
| Thurs, 9/14 | Lecture 7: Linear and Ensemble Models | pptx | pdf | |
| Mon, 9/18 | Workshop 5: scikit-learn | materials | |
| Tues, 9/19 | Lecture 8: Ethics in Data Science | pptx | pdf | |
| Thurs, 9/21 | Lecture 9: Graphs | pptx | pdf | |
| Mon, 9/25 | Workshop 6: Azure ML | materials | |
| Tues, 9/26 | Lecture 10: Spectral Clustering | pptx | pdf | |
| Tues, 9/26 | Homework 2 Due | ||
| Thurs, 9/28 | Lecture 11: Semi-supervised Learning on Graphs | pptx | pdf | |
| Thurs, 9/28 | Homework 3 Released | pdf | handout | |
| Mon, 10/2 | Workshop 7: MLFlow | materials | |
| Tues, 10/3 | Lecture 12: Embeddings I: Metric Learning | pptx | pdf | |
| Thurs, 10/5 | Lecture 13: Embeddings II: Sparse & Kernel PCA, and Dictionary Learning | pptx | pdf | |
| Mon, 10/9 | Workshop 8: OpenCV | materials | |
| Tues, 10/10 | Workshop 9: Weights & Biases // Midterm Review | materials | |
| Tues, 10/10 | Homework 3 Due | ||
| Thurs, 10/12 | Midterm Exam | ||
| Thurs, 10/12 | Homework 4 Released | pdf | handout | |
| Mon, 10/16 | No Class - IOB AI/ML Symposium | ||
| Tues, 10/17 | No Class - IOB AI/ML Symposium | ||
| Tues, 10/17 | Final Project Proposals Due | ||
| Thurs, 10/19 | Workshop 10: PySpark | materials | |
| Thurs, 10/19 | Lecture 14: Kernel Methods and Support Vector Machines | pptx | pdf | |
| Mon, 10/23 | Workshop 11: TensorFlow | materials | |
| Tues, 10/24 | Lecture 15: Randomized SVD | pptx | pdf | |
| Thurs, 10/26 | Lecture 16: Optimization | pptx | pdf | |
| Mon, 10/30 | Workshop 12: Dask | materials | |
| Tues, 10/31 | Lecture 17: Neural Networks | pptx | pdf | |
| Tues, 10/31 | Homework 4 Due | ||
| Tues, 10/31 | Final Project Update #1 Due | ||
| Thurs, 11/2 | Workshop 13: Natural Language Processing | materials | |
| Thurs, 11/2 | Lecture 18: Backpropagation | pptx | pdf | |
| Thurs, 11/2 | Homework 5 Released | pdf | handout | |
| Mon, 11/6 | Workshop 14: GitHub Codespaces | materials | |
| Tues, 11/7 | Lecture 19: Convolutional Neural Networks (CNNs) | pptx | pdf | |
| Thurs, 11/9 | Workshop 15: Seaborn | materials | |
| Thurs, 11/9 | Lecture 20: Recurrent Neural Networks (RNNs) | pptx | pdf | |
| Mon, 11/13 | Workshop 16: Keras | materials | |
| Tues, 11/14 | Lecture 21: Autoencoders | pptx | pdf | |
| Tues, 11/14 | Final Project Update #2 Due | ||
| Thurs, 11/16 | Lecture 22: Transformers | pptx | pdf | |
| Mon, 11/20 | Workshop 17: Matplotlib | materials | |
| Tues, 11/21 | Workshop 18: Prophet | materials | |
| Tues, 11/21 | Lecture 23: Generative AI | pptx | pdf | |
| Tues, 11/21 | Homework 5 Due | ||
| Thurs, 11/23 | No Class - Thanksgiving Break | ||
| Mon, 11/27 | Final Project Presentations | ||
| Tues, 11/28 | Final Project Presentations | ||
| Thurs, 11/30 | Workshop 19: RAPIDS | materials | |
| Thurs, 11/30 | Final Project Presentations | ||
| Mon, 12/4 | Final Project Presentations |