Series: Introduction to Machine Learning with Python Online
In this workshop, we will explore the fundamentals of machine learning using scikit-learn. Participants will learn essential techniques for data preparation, model building, and evaluation through practical, hands-on exercises. This curriculum is designed for beginners, providing a clear and straightforward introduction to machine learning concepts. By the end of the workshop, you will have an understanding of how to apply these skills to real-world problems, regardless of your prior programming experience.
This is a three-part workshop series (please register for each session separately):
- Part 1: Introduction to Machine Learning and Supervised Methods
- Part 2: Ensemble Methods
- Part 3: Unsupervised Methods and Neural Networks
- Date:
- Tuesday, September 30, 2025
- Time:
- 9:30am - 11:00am
- Time Zone:
- Eastern Time - US & Canada (change)
- Campus:
- Virtual Workshop
- Audience:
- Alumni Faculty Pittsburgh community Staff Students
- Categories:
- Artificial Intelligence Information & Data Literacy CC Open Science Working With Data and Code
- Online:
- This is a virtual event. A URL to participate will be sent via a reminder email 24 hours before the event.
Virtual Workshop Information:
- The link to join this event will be found in your confirmation email and in the reminder email sent 24 hours before the event.
- Please join a few minutes early to ensure that your audio setup is working correctly.
- All events are shown in Pittsburgh time. Visit this time zone converter to see when this event will take place in your time zone.
Automated notetaking tools and recordings not initiated by the instructor are generally not permitted in workshops. However, participants may request permission to use approved tools, such as Zoom AI Companion, for accommodation purposes. To ensure appropriate arrangements, please submit these requests to instructors at least 24 hours prior to the workshop.
Workshops and events for Carnegie Mellon University Libraries are open to all, regardless of race, color, national origin, sex, disability, age, sexual orientation, gender identity, religion, creed, ancestry, belief, veteran status or genetic information. All participants are required to follow the Code of Conduct.
If you require accessibility accommodations, please contact the event organizer.
