Foundations of AI

King's College London

Course Description

  • Course Name

    Foundations of AI

  • Host University

    King's College London

  • Location

    London, England

  • Area of Study

    Computer Science

  • Language Level

    Taught In English

  • Course Level Recommendations

    Lower

    ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.

    Hours & Credits

  • Contact Hours

    45
  • Recommended U.S. Semester Credits
    3 - 4
  • Recommended U.S. Quarter Units
    4.5 - 6
  • Overview

    Foundations of AI is an introductory course which explores the fundamental methods and mathematical framework underpinning Artificial Intelligence (AI). This course provides students with a deep understanding of AI technologies, including machine learning, neural networks, probability theory, game theory and logic programming.

    Students will gain insights to the potential of AI in revolutionizing industries such as healthcare, finance, sustainability, and transportation. They will explore how AI can automate tasks, make predictions, and assist in decision-making.

    The course will also emphasize the limitations and challenges of AI technologies. It covers issues related to bias and fairness in AI algorithms, the need for responsible AI development, and the computational limitations of AI methods.

    By the end of the module, students should have:

    A well-rounded understanding of AI and its immense potential

    An understanding of the critical need to navigate its limitations responsibly

    Skills to contribute to the development and deployment of AI technologies.

Course Disclaimer

Courses and course hours of instruction are subject to change.

Eligibility for courses may be subject to a placement exam and/or pre-requisites.

Some courses may require additional fees.

Availability of courses is based on enrollment numbers. All students should seek pre-approval for alternate courses in the event of last minute class cancellations

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