Artificial Intelligence Fundamentals


Learn the fundamentals of Artificial Intelligence (AI), and apply them.

Design intelligent agents to solve real-world problems including, search, games, machine learning, logic, and constraint satisfaction problems. What do self-driving cars, face recognition, web search, industrial robots, missile guidance, and tumour 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 the Artificial Intelligence MicroMasters® Programme, offered through the edX® platform.

Associated Programmes:
MicroMasters® Programme: Artificial Intelligence

Associated Courses:
Machine Learning
Master the essentials of machine learning and algorithms to help improve learning from data without human intervention.
View the Machine Learning course

Learn the core techniques for representing robots that perform physical tasks in the real world.
View the Robotics course

Animation and CGI Motion
Learn the science behind movie animation from the Director of Columbia’s Computer Graphics Group.
View the Animation and CGI Motion course

Students are required to have some basic of Python programming and an understanding of probability. Homework assignments will have a programming component in Python. The course offers an excellent opportunity for students to dive into Python while solving AI problems and learning its applications.

  • Linear algebra (vectors, matrices, derivatives)
  • Calculus
  • Basic probability theory
  • Python programming

edX® and MicroMasters® are registered trademarks of edX® Inc. All Rights Reserved.

  • Programme duration
    12 weeks
  • Estimated effort
    8-10 hours per week
  • Fee
  • Institution
  • Language
Start Dates
  • 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

Course 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

Arlene Lanser

Pearson Student Advisor