Introduction to Artificial Intelligence


Units: 12


Driven by the combination of increased access to data, computational power, and improved sensors and algorithms, artificial intelligence (AI) technologies are entering the mainstream of technological innovation. These technologies include search, machine learning, natural language processing, robotics and computer vision.

The course begins by describing what the latest generation of artificial intelligence techniques can actually do. After an introduction of some basic concepts and techniques, the course illustrates both the potential and current limitations of these techniques with examples from a variety of applications.  We spend some time on understanding the strengths and weaknesses of human decision-making and learning, specifically in combination with AI systems. Exercises will include hands-on application of basic AI techniques as well as selection of appropriate technologies for a given problem and anticipation of design implications.  In a final project, groups of students will participate in the creation of an AI-based application.

Students cannot take this course as pass/no pass or audit the class.

Learning Outcomes

The main learning objectives of the course are to:

  1. Identify problems where artificial intelligence techniques are applicable
  2. Apply selected basic AI techniques; judge applicability of more advanced techniques.
  3. Participate in the design of systems that act intelligently and learn from experience.

Prerequisites Description

This course is primarily aimed at students with technical backgrounds who wish to design and develop products and services using AI. A background in basic statistics is required for the course (95796). Students need at least a basic knowledge of Python to complete the assignments for this course. Students who have not taken 90-812 or 95-888 or have equivalent background will be required to complete supplementary work to learn Python at the beginning of the course.