Fundamentals of AI
| Structure Type: | Study unit |
|---|---|
| Code: | H2C1105 |
| Curriculum: | H2C 2020 |
| Level: | Continuing Education etc. |
| Year of Study: | 1 (2020-2021) |
| Semester: | Spring |
| Credits: | 3 cr |
| Responsible Teacher: | Salonen, Klaus |
| Language of Instruction: | English |
Courses During the Academic Year 2020-2021
| Impl. | Group(s) | Study Time | Teacher(s) | Language | Enrolment |
|---|---|---|---|---|---|
| 3001 | H2C-20 | 2020-11-13 – 2020-12-19 | Kenneth Norrgård, Klaus Salonen | English | 2020-08-10 – 2020-08-31 |
Learning Outcomes
After the course the student will be familiar with the concepts of Artificial Intelligence (AI), Machine learning (ML), and Artificial Neural Networks (ANN). The student will also understand the workflow from problem to solution using data, selecting algorithms and creating predictive models with tools such as Tensorflow, Theano, and Scikit-learn. An introduction to Python programming language is included.
Student's Workload
A total of 81h split up evenly on weekly activities.
Prerequisites / Recommended Optional Courses
For Python some basic programming skill or at least a rudimentary understanding is helpful but not mandatory. For AI an understanding of Python and statistical methods is helpful but not mandatory.
Regional Impact
The demand for AI fluent individuals is high regionally, nationally, and internationally. The gap between demand and supply of qualified personel is also increasing and therefore the impact of this course is high especially for regional companies.
Internationality
The demand for qualified personel is for the foreseeable future on the rise regionally, nationally, and internationally.
Mode of Delivery / Planned Learning Activities and Teaching Methods
This is an online course with selected hand-picked courses for personal use and with the possibility to do some hands-on, unsupervised exercises. There are no on-campus lectures for this course.
Assessment Methods
Quizzes.