Individual Course
Principles of AI
Course Length
-
3 hours
Featuring faculty from:
Harvard Faculty of Arts & Sciences
Enroll as a team
Pricing Options Available
Contact UsEnroll as a team
Pricing Options Available
Contact UsExpectations for employees to use AI at work are rapidly rising but most teams still don’t understand how AI works, what makes it reliable, or how to apply it responsibly.
Taught by Harvard Professor Dustin Tingley, this short, modular course cuts through the hype with a practical foundation in AI beyond generative tools, including machine learning, NLP, neural networks, and computer vision.
Across four bite-sized sections, learners explore how AI is trained and why data quality and strategy determine success. Real-world risk and resilience use cases show how AI can shift organizations from reactive to proactive. Learners will leave this course with actionable guidance on fairness, bias, governance, and security, empowering learners to lead ethical AI adoption with employee buy-in and effective upskilling.
Self-Guided
Harvard Online
Industries:
- Technology
- Consumer Products
- Government
- Consulting
- Learning Outcome
Understand AI foundations
- Learning Outcome
Assess data readiness for AI success
- Learning Outcome
Lead responsible AI adoption at work
Your Instructor
Dustin Tingley
Thomas D. Cabot Professor of Public Policy with a joint appointment in the Harvard Kennedy School of Public Policy and Harvard Government Department
Dustin Tingley is a data scientist at Harvard University. He is the Thomas D. Cabot Professor of Public Policy with a joint appointment in the Harvard Kennedy School of Public Policy and Harvard Government Department. Professor Tingley is Deputy Vice Provost for Advances in Learning and helps to direct Harvard's education focused data science and technology team. He has helped a variety of organizations use the tools of data science and helped to develop machine learning algorithms and accompanying software for the social sciences. He has written on a variety of topics using data science techniques, including education, politics, and economics.
- Learn from real case studies
- Do it on your own time
- Complete the course, add it to your resume
- Be part of the Harvard Community
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