One algorithm at a time
This Program is Perfect For
- Professionals seeking to leverage contemporary machine learning techniques in their work
- Learners with solid programming and quantitative foundations ready to level up
- Lifelong learners seeking a flexible, career-relevant credential
Specialization description
Machine learning technology to stay competitive
This comprehensive Machine Learning with Python program combines current machine learning techniques and practical Python programming skills to help working professionals gain a competitive edge.
Fall 2025 AI Workshops and Course Flyer | Download
Skills you will gain
- Mastery of essential machine learning concepts and algorithms
- Proficiency in Python programming for data analysis and ML applications
- Hands-on experience with real-world datasets and industry-relevant projects
- Skills in data visualization and interpretation of complex ML results
Bridge theoretical knowledge and practical application.
- Implement ML solutions to solve complex business problems
- Enhance decision-making processes with data-driven insights
- Develop innovative AI-powered applications
- Improve existing systems with advanced analytics and predictive modeling
Whether you're a software engineer, data analyst, or business professional, this program will equip you with the tools to leverage machine learning in your field. Boost your career prospects, drive innovation in your organization, and position yourself at the forefront of the AI revolution.
Learning Outcomes
Students who complete this program will be able to:
- Develop and deploy Python scripts for data manipulation, statistical analysis, and machine learning tasks
- Implement Python-based algorithms for machine learning applications, including regression, classification, clustering, and neural networks.
- Identify and formulate machine learning problems, applying both supervised and unsupervised learning techniques.
- Evaluate the performance of machine learning models using cross-validation and practical datasets, interpreting results to improve model accuracy and efficiency.
Courses
Program Requirements:
- 6 unit | 2 required courses
| Title | units | Fall | Spring | Summer | Winter |
|---|---|---|---|---|---|
| Python for Machine Learning | 3.0 | Flexible | |||
| Introduction to Machine Learning | 3.0 | Flexible | Flexible |
| Title | units | Fall | Spring | Summer | Winter |
|---|---|---|---|---|---|
| Specialization in Machine Learning with Python Completion Fee |
1. Required Courses:
- Flexible Attend in person or via Zoom at scheduled times.
| Date | Start Time | End Time | Meeting Type | Location |
|---|---|---|---|---|
| Mon, 02-09-2026 | 9:00am | 3:00pm | Flexible | SANTA CLARA / REMOTE |
| Tue, 02-10-2026 | 9:00am | 3:00pm | Flexible | SANTA CLARA / REMOTE |
| Wed, 02-11-2026 | 9:00am | 3:00pm | Flexible | SANTA CLARA / REMOTE |
| Thu, 02-12-2026 | 9:00am | 3:00pm | Flexible | SANTA CLARA / REMOTE |
| Fri, 02-13-2026 | 9:00am | 3:00pm | Flexible | SANTA CLARA / REMOTE |
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
- Flexible Attend in person or via Zoom at scheduled times.
| Date | Start Time | End Time | Meeting Type | Location |
|---|---|---|---|---|
| Tue, 01-13-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Tue, 01-20-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Tue, 01-27-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Tue, 02-03-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Tue, 02-10-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Tue, 02-17-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Tue, 02-24-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Tue, 03-03-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Tue, 03-10-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Tue, 03-17-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
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.
Programming Tools: Current version of Python with ability to install packages as needed.
- Flexible Attend in person or via Zoom at scheduled times.
| Date | Start Time | End Time | Meeting Type | Location |
|---|---|---|---|---|
| Wed, 04-08-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Wed, 04-15-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Wed, 04-22-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Wed, 04-29-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Wed, 05-06-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Wed, 05-13-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Wed, 05-20-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Wed, 05-27-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Wed, 06-03-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Wed, 06-10-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
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.
Programming Tools: Current version of Python with ability to install packages as needed.
2. Completion Review:
Please enroll in the Machine Learning with Python Completion Fee only when all of the specialization requirements have been met and your final grades are posted.
Requisite knowledge
We recommend that you:
- Have reasonably good programming and debugging skills that are beyond the basic or beginner level.
- Are comfortable with basic knowledge of algebra, calculus, probability, and statistics.
Establish Candidacy
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