Artificial Intelligence (AI)

edX Artificial Intelligence (AI)

Platform
edX
Provider
Columbia University
Effort
8 to 10 hours per week
Length
12 weeks
Language
English
Credentials
Paid Certificate Available
Part of
Course Link
Overview
What do self-driving cars, face recognition, web search, industrial robots, missile guidance, and tumor detection have in common?

They are all complex real world problems being solved with applications of intelligence (AI).

This course will provide a broad understanding of the basic techniques for building intelligent computer systems and an understanding of how AI is applied to problems.

You will learn about the history of AI, intelligent agents, state-space problem representations, uninformed and heuristic search, game playing, logical agents, and constraint satisfaction problems.

Hands on experience will be gained by building a basic search agent. Adversarial search will be explored through the creation of a game and an introduction to machine learning includes work on linear regression.

This course is part of a MicroMasters program. If you complete all courses in the MicroMasters program in 2018, GE will guarantee you an interview in Boston for an internship or full-time role. Open to Massachusetts residents only.

What you'll learn
  • Introduction to Artificial Intelligence and intelligent agents, history of Artificial Intelligence
  • Building intelligent agents (search, games, logic, constraint satisfaction problems)
  • Machine Learning algorithms
  • Applications of AI (Natural Language Processing, Robotics/Vision)
  • Solving real AI problems through programming with Python
Syllabus
Week 1:
Introduction to AI, history of AI, course logistics
Week 2: Intelligent agents, uninformed search
Week 3: Heuristic search, A* algorithm
Week 4: Adversarial search, games
Week 5: Constraint Satisfaction Problems
Week 6: Machine Learning: Basic concepts, linear models, perceptron, K nearest neighbors
Week 7: Machine Learning: advanced models, neural networks, SVMs, decision trees and unsupervised learning
Week 8: Markov decision processes and reinforcement learning
Week 9: Logical Agent, propositional logic and first order logic
Week 10: AI applications (NLP)
Week 11: AI applications (Vision/Robotics)
Week 12: Review and Conclusion

Taught by
Professor Ansaf Salleb-Aouissi
Author
edX
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