Current
Intermediate
Artificial Intelligence: Principles and Techniques (XCS221)
Stanford Online · Stanford School of Engineering · Updated March 2026
Platform rating
4.6/5
AI Tutor Rating
8.6/10
Duration
10-15 hrs/week
Classes
53
Core AI course on problem solving, reasoning, learning, search, planning, Bayesian networks, reinforcement learning, and AI societal impact.
What you'll get
Implement foundational AI algorithms
Apply search and planning to practical tasks
Model uncertainty with Bayesian and MDP methods
Evaluate AI systems through technical and societal lenses
Fit
Best for
Developers
AI Engineers
Data Scientists
Technical Builders
Not ideal for
Learners seeking only entry-level overviews
Prerequisites & pricing
Prerequisites
Python, calculus/linear algebra, probability
Pricing
$1,950
Certification
Certificate
Growth Leverage: Completing this course positions individuals for roles such as Machine Learning Engineer, Data Scientist, or AI Researcher, enabling them to pursue certifications like the Microsoft Azure AI Engineer Associate. It opens doors to opportunities in tech companies, startups, and research institutions focusing on AI applications.
Skills Value: The skills learned justify higher salaries, with Machine Learning Engineers earning an average of $112,000 annually, as they can solve complex problems in search optimization, decision-making under uncertainty, and evaluate AI systems, meeting the high market demand for AI expertise.
XCS221
Foundational AI
Search
Reinforcement Learning