Curricula
Description
| IN00CS91 | Basics of Machine Learning (5 cr) |
| Prerequisites | This course is arranged in Finnish |
| Objectives | A student knows what can be done with machine learning and what is not possible. The student knows some practical machine learning solutions. The student can implement simple machine learning algorithms with Python programming language. The student can use Python’s machine learning libraries for processing data and for drawing some conclusions based on data. The student understands the operating principle of neural network and can teach and use a neural network. |
| Content | Artificial Intelligence, machine learning, practical machine learning solutions. Linear matrix operations, derivative and gradient as tools of machine learning. Basics of Python programming and primary Python libraries for machine learning. Neural Networks. |
| Recommended optional programme components | If necessary, the student advisor will recommend optional programme components for each student based on their individual study plan. |
| Accomplishment methods | Not applicable |
| Execution methods | Not applicable |
| Materials | Not applicable |
| Literature | Not applicable |
| Evaluation Criteria | 0-5 |
| Evaluation Criteria |
satisfactory (1-2) The student is able to use the basic concepts learned in the course. The student recognizes the phenomena related to the course. The student is able to satisfactorily express the definitions of the course. The student completes the given tasks with guidance and knows the different procedures, but doesn’t know how to justify their choices. The student knows how to give and receive feedback by examining and evaluating from own perspective. The student has interaction skills and takes resonsibility for own studying. good (3-4) The student can apply the basic concepts learned in the course. The student analyses the phenomena related to the course and understands well the definitions of the course. The student solves the given tasks and uses the different procedures, knowing how to justify the choices. The student is able to give and receive feedback actively and constructively, looking and evaluating from own and environment perspective. The students have good interaction skills and are ready to develop themselves in their studies. excellent (5) The student can use the concepts learned in the course. The student understands the phenomena related to the course and can connect the definitions with professional context. The student solves excellently the given tasks and uses the different procedures creatively, evaluating the justification of the choices. The student is able to give and receive feedback actively and constructively, looking and evaluating from own and professional study field perspective.The student is capable of professional development. |
| Assessment Frameworks | Not applicable |
| Further Information | - |
| Responsible persons | Not applicable |
| Links | Not applicable |
Implementations
Show old implementations
- 28.08.2023 - 22.10.2023 (IN00CS91-3003 | TVT22SPL)
- 26.08.2024 - 27.10.2024 (IN00CS91-3004 | TVT23SPL)
20.5.2024 10:34:05