Kuva: Reaktor
A massive open online course
Take our hugely popular AI course!
What is artificial intelligence? How does it affect your work and life? How will artificial intelligence develop? The course aims to make AI more understandable. You do not need an in-depth knowledge of maths or programming skills to take the course. You can start the course flexibly in the MOOC learning environment and complete it at your convenience. For further information, please see the course description.
ALSO NOTE: Are you wondering what it takes to complete the course? Click here for frequently asked questions (e.g., information on course assessment, duration and credits). You can also ask questions (e.g., about course assignments) in the course chat room .
Ilmoittautuminen ja opintomaksu
Kuvaus
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
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.
No formal prerequisites beyond high-school mathematics (basic arithmetics with fractions)
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?
- motivation
- 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
Machine learning
- nearest neighbor classifier
- linear regression
- logistic regression
Neural networks
- concepts of neural computation
- learning in neural networks
- perceptron classifier
Implications
- 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)
Taking this course does not give students access to a University of Helsinki user account. If you want to view and share information about your studies after completing the course, sign up for the Oma Opintopolku -service maintained by the Finnish National Agency for Education. The ECTS will be displayed within two days in the Oma Opintopolku -service after credits have been registered to the University of Helsinki. To register for the Oma Opintopolku – service you must identify yourself by using Finnish bank identification codes, mobile certificate or certificate card.
Questions regarding the course:
- Questions regarding the learning environment: mooc@cs.helsinki.fi
- Questions about registering at the Open University: avoinyo-tietojenkasittelytiede@helsinki.fi
- 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
- If you have questions about DEFA studies, please contact DEFA-help@cs.helsinki.fi.
- If you have questions about the content of the course, please contact the teacher in charge of the course: teemu.roos@cs.helsinki.fi
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 in the online learning environment of the course at https://www.elementsofai.com/
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.