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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.
In this Artificial Intelligence (AI) course, part of the Artificial Intelligence MicroMasters program from Columbia University - ColumbiaX 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.
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
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.
The Artificial Intelligence (AI) programme is part of the Artifiacial Inteligence MicroMasters Programme.
Programme Structure
Courses include:
- Intelligent agents, uninformed search
- Heuristic search, A* algorithm
- Adversarial search, games
- Constraint Satisfaction Problems
- Machine Learning: Basic concepts, linear models, perceptron, K nearest neighbors
- Machine Learning: advanced models, neural networks, SVMs, decision trees and unsupervised learning
- Markov decision processes and reinforcement learning
Key information
Duration
- Part-time
- 3 months
- 8 hrs/week
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
Campus Location
- Manhattan, United States
Disciplines
Computer Sciences Artificial Intelligence Machine Learning View 213 other Short Courses in Machine Learning in United StatesWhat students do after studying
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Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
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
Tuition Fees
Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
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International Applies to you
Applies to youNon-residentsFree - Out-of-StateFree
Additional Details
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Funding
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