The course is a MOOC (Massive Open Online Course) course available for everyone free of charge.
You can start the course flexibly and complete it at your convenience. You can study the course independently at https://www.elementsofai.com/
If you complete the course and wish to have the credits entered in the University of Helsinki’s student records, you must register for the course at the Open University after completing it. You can find the link for registration form by going to My profile. All students of University of Helsinki have to register via The University of Helsinki Open University to get the ECTS registered.
- Please note that the course registration form is open for a pre-defined period onlye (31th of July 2019)
- If you enter erroneous information when registering, we cannot register your credits.
- The ECTS credits are possible to people who have a Finnish social security number (=Personal identity number). Information on Finnish personal identity numbers/codes.
The course credits will be registered within six weeks of registration. Please note that due to the large number of students taking the course, the registration process cannot be expedited.
If you have questions about registering at the Open University, please contact email@example.com
If you are completing DEFA (Digital Education For All) studies, Elements of AI is one of the courses that can be completed for application purposes; please see information in Finnish at https://www.helsinki.fi/fi/projektit/digital-education-for-all/opiskelijaksi. The course can be completed flexibly, so please plan your course path and its completion so as to meet the application criteria for the DEFA project. Queries about DEFA studies can be sent to DEFAfirstname.lastname@example.org.
We reserve the right to change our study programme.
Optional course in the Bachelor Programme of Computer Science
- suitable for all students in any study programme
- the target audience is especially students with little or no computer science studies
No formal prerequisites beyond high-school mathematics (basic arithmetics with fractions)
After the course, if the student wishes to continue learning about AI, we recommend learning some programming and taking introductory AI courses. These courses are mainly held at the faculty:
- a follow-up MOOC "AI Programming" will begin in Spring 2019
- DATA15001 Introduction to AI is a closely related intermediate course that also includes programming exercises on the same topics
- DATA11001 Introduction to Data Science (advanced course)
- DATA11002 Introduction to Machine Learning (advanced course)
- closely related Bachelor programmes include the Bachelor of Science and Bachelor of Computer Science
- closely related Master's programmes include the Master of Data Science and Master of Computer Science
After 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
- any stage of studies
- the course is offered continuously
- the course can be started at any time, and completed at any pace
- recommended duration is six weeks
What is AI?
- definition of AI
- philosophy of AI
AI problem solving
- formulating and solving problems using state diagrams
- formulating simple games (tic-tac-toe or chess) as game trees
- solving game trees using the minimax algorithm
Real world AI
- expressing uncertainty using probability
- probabilities and odds
- Bayes formula
- nearest neighbor classifier
- linear regression
- logistic regression
- concepts of neural computation
- learning in neural networks
- perceptron classifier
- public perception of AI
- critical evaluation of claims made about AI (e.g., singularity, AI winter)
- societal implications and ethics of AI
Exercises including multiple choice quizzes, numerical exercises, and questions that require a written answer
The multiple choice and numerical exercises are automatically checked
The exercises with written answers are reviewed by other students (peer grading) and in some cases by the instructors
The course material is available at https://course.elementsofai.com/
- The course material contains text and interactive elements
- The exercises are designed to challenge the student to re-read the material and access further sources enough to be able to produce an answer
- Successful completion requires 90% completed exercises and minimum 50% correctness
- Only one attempt is allowed in the multiple choice quizzes and numerical exercises
- Exercises with written answers are accepted or rejected based on the reviews: in case of rejection, another attempt is allowed (as many times as required)
Questions about registering at the Open University: email@example.com
Other questions about the course: https://spectrum.chat/elementsofai?tab=posts
You can also check out the FAQ page https://www.elementsofai.com/faq to look for a ready-made answer to your question.
Taking this course does not give students access to a University of Helsinki user account. Once your credits have been registered, you will receive a confirmation message to the email address you have provided.
Teemu Roos. The Elements of AI course is created by Reaktor and the University of Helsinki.
The course is part of the subject studies in Computer Science.