Elements of AI - Introduction to AI

Course guarantor:

Lecturer:

Tutor:

Supervisor:

Rectorate of CTU

Synopsis:

The Elements of AI is a series of free online courses created by Reaktor and the University of Helsinki. We want to encourage as broad a group of people as possible to learn what AI is, what can (and can’t) be done with AI, and how to start creating AI methods. The courses combine theory with practical exercises and can be completed at your own pace. An Introduction to AI is a free online course for everyone interested in learning what AI is, what is possible (and not possible) with AI, and how it affects our lives – with no complicated math or programming required. https://www.elementsofai.com/

Requirements:

Syllabus of lectures:

Syllabus of tutorials:

Study Objective:

After successfully completing the course the student will be able to:

Identify autonomy and adaptivity as key concepts of AI

Distinguish between realistic and unrealistic AI (science fiction vs. real life)

Express the basic philosophical problems related to AI including the implications of the Turing test and Chinese room thought experiment

Formulate a real-world problem as a search problem

Formulate a simple game (such as tic-tac-toe) as a game tree

Use the minimax principle to find optimal moves in a limited-size game tree

Express probabilities in terms of natural frequencies

Apply the Bayes rule to infer risks in simple scenarios

Explain the base-rate fallacy and avoid it by applying Bayesian reasoning

Explain why machine learning techniques are used

Distinguish between unsupervised and supervised machine learning scenarios

Explain the principles of three supervised classification methods: the nearest neighbor method, linear regression, and logistic regression

Explain what a neural network is and where they are being successfully used

Understand the technical methods that underpin neural networks

Understand the difficulty in predicting the future and be able to better evaluate the claims made about AI

Identify some of the major societal implications of AI including algorithmic bias, AI-generated content, privacy, and work

Study materials:

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans: