Sara Saatchi

This class is offered in an online synchronous format. Students are expected to log into this course via Canvas at the start time of scheduled meetings and participate via Zoom, for the duration of each scheduled class meeting.

To see all meeting dates, click "Full Schedule" below.

Students are expected to have computers with Python 3.x, Jupyter Notebooks, libraries: Pandas, Matplotlib and Numpy installed. Installing the Anaconda distribution of Python, gives access to Jupyter Notebooks and all the required libraries. Instructions will be provided.

You will be granted access in Canvas to your course site and course materials approximately 24 hours prior to the published start date of the course.

Required Text:
"Murach's Python for Data Science", 2nd Edition, by Scott McCoy, published by Murach Books, May 2024. ISBN 978-1943873173

Recommended Text: 
"Python for Data Analysis", 3rd Edition, by Wes McKinney, published by O'Reilly Media, Inc. - ISBN 9781098103989

11/7/25: Change in start time. See full schedule for details.

This class meets simultaneously in a classroom and remotely via Zoom. Students are expected to attend and participate in the course, either in-person or remotely, during the days and times that are specified on the course schedule. Students attending remotely are also strongly encouraged to have their cameras on to get the most out of the remote learning experience. Students attending the class in-person are expected to bring a laptop to each class meeting.

To see all meeting dates, click "Full Schedule" below.

Electronic Course Materials: You will be granted access in Canvas to your course site and course materials approximately 24 hours prior to the published start date of the course.

Required Text: Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow; Aurelien Geron; O'Reilly Media Inc.; 2022. ISBN: 9781098122461

Recommended Text: Hands-On Machine Learning with Scikit-Learn and PyTorch: Concepts, Tools, and Techniques to Build Intelligent Systems; Aurélien Géron; O'Reilly Media Inc.; 2025. ISBN: 979-8341607989

Python Data Science Handbook; Jake VanderPlas; O'Reilly Media Inc.; 2023. ISBN: 9781098121228

Machine Learning with Python Cookbook; Gallatin and Albon; O'Reilly Media Inc.; 2023. ISBN: 9781098135690

Introduction to Machine Learning with Python; Muller and Guido; O'Reilly Media Inc.; 2023. ISBN: 9781449369897

This class meets simultaneously in a classroom and remotely via Zoom. Students are expected to attend and participate in the course, either in-person or remotely, during the days and times that are specified on the course schedule. Students attending remotely are also strongly encouraged to have their cameras on to get the most out of the remote learning experience. Students attending the class in-person are expected to bring a laptop to each class meeting.

To see all meeting dates, click "Full Schedule" below.

You will be granted access in Canvas to your course site and course materials approximately 24 hours prior to the published start date of the course.

Required Textbook: Hands-On Machine Learning with Scikit-Learn and PyTorch: Concepts, Tools, and Techniques to Build Intelligent Systems; Aurélien Géron; O'Reilly Media Inc.; 2025. ISBN: 979-8341607989

Recommended Textbooks: 

Python Data Science Handbook; Jake VanderPlas; O'Reilly Media Inc.; 2023. ISBN: 9781098121228

Machine Learning with Python Cookbook; Gallatin and Albon; O'Reilly Media Inc.; 2023. ISBN: 9781098135690

Introduction to Machine Learning with Python; Muller and Guido; O'Reilly Media Inc.; 2023. ISBN: 9781449369897

Online Self-Paced courses have a structured learning environment where students are allowed to complete the work at their own pace. Students may complete the coursework early or use the entire duration of the course. This course is largely self-study with instructor guidance and includes online learning modules, assignments, and/or quizzes. All course materials and assignments will be available at the beginning of the course on Canvas, our learning management system.

For this section, student access begins on January 6, but you may still enroll until February 10. All course work must be completed by 11:59 pm on April 7, 2026.

Access to a computer with Python version 3.6 or higher and Jupyter Notebook is required. The recommended software to obtain the required tools for this course is Anaconda, free Individual Edition: https://www.anaconda.com/products/individual

Electronic Course Materials: You will be granted access in Canvas to your course site and course materials approximately 24 hours prior to the published start date of the course.

Recommended Text:
Learn to Program with Python 3: A Step-by-Step Guide to Programming, 2nd edition, by Irv Kalb, Apress. ISBN-13: 978-1484238783 ISBN-10: 9781484238783

Murach's Python Programming (2nd Edition), Authors: Joel Murach, Michael Urban Publication Date: 2021-04-01 ISBN: 9781943872749

Think Python, Authors: Allen B. Downey Publisher: "O'Reilly Media, Inc." Publication Date: 2015-12-02 ISBN: 9781491939413

Python Programming for the Absolute Beginner, Authors: Michael Dawson Publisher: Course Technology Publication Date: 2003-01-01 ISBN: 9781592000739