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

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

View course schedule

1. Required Courses:
Title units Fall Spring Summer Winter
Introduction to Machine Learning 3.0 Flexible
Python for Machine Learning 3.0 Flexible
2. Completion Review:
Title units Fall Spring Summer Winter
Specialization in Machine Learning with Python Completion Fee

1. Required Courses:

AISV.X400
$980
  • Flexible Attend in person or via Zoom at scheduled times.
Schedule
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.

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Prerequisites / Skills Needed

Prerequisites:

  • DBDA.X427: Python for Machine Learning

Skills Needed:

  • Familiarity with Google Colaboratory and Jupyter Notebooks
  • Reasonably good programming/debugging skills beyond the basic or beginner level
  • Familiarity with Python programming, NumPy, and Pandas
  • Comfortable with basic knowledge of algebra, calculus, probability and statistics
Spring
DBDA.X427
$980 (Estimated Cost)
Currently no classes scheduled. Would you like to be notified when a class is available?
Winter

2. Completion Review:

O-CE0533
$50
Schedule
 

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.
Demo