Max amount of FITech students: 100 adult learners
Course contents
On this course, we will cover topics such as
- algorithmic thinking
- probability theory and Bayesian concepts
- concepts and review of machine learning algorithms
- game theory and decision making
- NLP workflow: text mining, word embedding, skip-grams, cbow
- programming tools: Jupyter and Spyder
- Keras and applications
- Scikit learn
- Orange data management tool
- ethical and societal challenges and categories of ethical challenges of AI
Learning outcomes
After completing the course, the student is able to:
- Define and explain various artificial intelligence (AI) concepts, challenges, and opportunities: e.g., problem-solving, knowledge representation, machine learning, decision-making, natural language processing, and expert systems.
- Explain fundamental algorithms and the related mathematical and programming concepts of AI.
- List applications of AI in various fields.
- Use AI software or tools for specific purposes.
- Recognize ethical problems related to AI and to suggest constructive solutions to those.
Completion methods
- Lectures (Mon-Thu) are voluntary exept for the first lecture.
- Team and/or individual exercises and quizzes.
- This course can be studied online with the given schedule (not on your own pace).
More information in University of Vaasa’s course page. Course schedule is available in Peppi, when implementation is published.
You can get a digital badge after completing this course.
