University IT
Machine Learning: A Beginner’s Guide
This class offers an option for in-classroom sessions. Participants attending an in-person class will need to adhere to the respiratory illness policies.
Learn about Machine Learning patterns and use cases in the real world, while getting a review of statistics and data analytics to be more data-minded, and helping to understand the Data Science process.
After this course, you will be able to:
- Describe the role of Machine Learning and where it fits into Information Technology strategies
- Explain the technical and business drivers that result from using Machine Learning
- Describe Supervised and Unsupervised learning techniques and usages
- Understand techniques like Classification, Clustering, and Regression
- Discuss how to identify which kinds of technique to be applied for a specific use case
Topic Outline:
- Course Introduction
- History and background of Machine Learning
- Compare Traditional Programming Vs Machine Leaning
- Supervised and Unsupervised Learning Overview
- Machine Learning patterns
- Classification
- Clustering
- Regression - Gartner Hype Cycle for Emerging Technologies
- Machine Learning offerings in Industry
- Hands-on exercise: Apply the Machine Learning Basics to real-life use case
- References and Next steps
University IT Technology Training classes are only available to Stanford University staff, faculty, or students. A valid SUNet ID is needed in order to enroll in a class.
Custom training workshops are available for this program
Technology training sessions structured around individual or group learning objectives. Learn more about custom training.
Special Group Rates
For groups of 5 or more, special rates are available. Please contact techtraining@stanford.edu for more details.
University IT Technology Training sessions are available to a wide range of participants, including Stanford University staff, faculty, students, and employees of Stanford Hospitals & Clinics, such as Stanford Health Care, Stanford Health Care Tri-Valley, Stanford Medicine Partners, and Stanford Medicine Children's Health.
Additionally, some of these programs are open to interested individuals not affiliated with Stanford, allowing for broader community engagement and learning opportunities.
