Course Schedule

31-May Synch	Introduction/What is Machine Learning? Readings Ch 1: “The Machine Learning Landscape” in Géron, Aurélien. (2019). Hands-On Machine Learning with Scikit-Learn, Keras and TensorFlow’ O’Reilly Media, Inc. 3–31. Jordan, Michael I. and Tom M. Mitchell. (2015). “Machine Learning: Trends, perspectives, and prospects” Science 349, 255—-60. http://www-cgi.cs.cmu.edu/~tom/pubs/Science-ML-2015.pdf
1-June Synch	Getting Started with Machine Learning Readings Ch 1: “Introduction” in Guido, Sarah and Andreas C. Muller. (2016). Introduction to Machine Learning with Python, O’Reilly Media, Inc. 1–25.
2-June Synch	Inspecting Data Readings Ch 2: End-to-End Machine Learning Project. in Géron, Aurélien. (2019). Hands-On Machine Learning with Scikit-Learn, Keras and TensorFlow’ O’Reilly Media, Inc. 33–66.
6-June Synch	Representing Data Readings Ch 4: “Representing Data/Engineering Features” in Guido, Sarah and Andreas C. Muller. (2016). Introduction to Machine Learning with Python, O’Reilly Media, Inc. 213–55
7-June Asynch	DataCamp Modules: Introduction to Python course (If Needed) “Introduction to AI” from AI Fundamentals course Data Manipulation with pandas Transforming Data Aggregating Data Slicing and Indexing Creating and Visualizing DataFrames (Optional) Writing Efficient Code with pandas (Optional)
8-June Synch	Evaluation Methods Readings Ch 5: “Model Evaluation and Improvement” in Guido, Sarah and Andreas C. Muller. (2016). Introduction to Machine Learning with Python, O’Reilly Media, Inc. 213–55
9-June Async	DataCamp Modules Cleaning Data in Python Common data problems Text and categorical data problems Advanced data problems Record linkage (optional) Preprocessing for Machine Learning in Python course Model Validation in Python course
13-June Synch	Supervised Learning (k-Nearest Neighbors and Linear Models) Readings Ch 2: “Supervised Learning” in Guido, Sarah and Andreas C. Muller. (2016). Introduction to Machine Learning with Python, O’Reilly Media, Inc. 27–70 Videos password is course number (no spaces)
14-June Asynch	DataCamp Modules “Basic Modeling in scikit-learn (through Feature Importances)” (In Model Validation in Python course) “Classification” (in Supervised Learning with scikit-learn course) “Regression” (in Supervised Learning with scikit-learn course) “Cross Validation” (In Model Validation in Python course)
15-June Synch	Supervised Learning (Naive Bayes Classifiers and Decision Trees, Support Vector Machines, and Uncertainty estimates from Classifiers) Readings Ch 2: “Supervised Learning” in Guido, Sarah and Andreas C. Muller. (2016). Introduction to Machine Learning with Python, O’Reilly Media, Inc. 70–106 and 121–131 Videos password is course number (no spaces)
16-June Asynch	DataCamp Modules “Classification and Regression Trees” (in Machine Learning with Tree-Based Models in Python course) Linear Classifiers in Python course
21-June Synch	Unsupervised Learning (Dimensionality Reduction & Feature Extraction, and Manifold Learning) Ethics (Part One) Readings Ch 3: “Unsupervised Learning” in Guido, Sarah and Andreas C. Muller. (2016). Introduction to Machine Learning with Python, O’Reilly Media, Inc. 133–170 Bostrom, Nick, and Eliezer Yudkowsky. (2014). “The ethics of artiﬁcial intelligence.” The Cambridge Handbook of Artiﬁcial Intelligence. 316–34. http://faculty.smcm.edu/acjamieson/s13/artificialintelligence.pdf Videos password is course number (no spaces)
22-June Synch	Unsupervised Learning (Clustering) Ethics (Part Two) Readings Ch 3: “Unsupervised Learning” in Guido, Sarah and Andreas C. Muller. (2016). Introduction to Machine Learning with Python, O’Reilly Media, Inc. 170–211 West, Sarah Myers, Meredith Whittaker, and Kate Crawford. (2019). “Discriminating systems: Gender, race and power in AI.” AI Now Institute, 1–33. https://ainowinstitute.org/discriminatingsystems.pdf Videos password is course number (no spaces)
23-June Asynch	DataCamp Modules Unsupervised Learning in Python course