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Artificial Intelligence with PythonLaajuus (5 cr)

Code: DT10075

Credits

5 op

Teaching language

  • English

Responsible person

  • Jyri Kemppainen
  • Radu Mariescu-Istodor

Objective

- You learn how an artificial neural network works
- You learn how to use ready-made libraries for artificial neural networks
- You learn how to apply artificial neural networks to problem solving

Content

Artificial neural networks
Python libraries for neural networks

Qualifications

- You master Python programming language, or
- You have completed Programming essentials in Python course
Recommended course: Data analytics with Python

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Enrollment

01.10.2022 - 26.02.2023

Timing

13.03.2023 - 25.05.2023

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Distance learning

Unit

Information and Communication Technologies (DATA)

Campus

Wärtsilä Campus Karjalankatu 3

Teaching languages
  • English
Seats

20 - 40

Degree programmes
  • Degree Programme in Business Information Technology
Teachers
  • Radu Mariescu-Istodor
  • Petri Laitinen
  • Jyri Kemppainen
Teacher in charge

Radu Mariescu-Istodor

Scheduling groups
  • Pienryhmä (schedulingGroup) 1 (Size: 20. Open UAS: 20.)
  • Pienryhmä (schedulingGroup) 2 (Size: 10. Open UAS: 0.)
Groups
  • KAKK23
    Karelia, Open UAS, All, Spring, 2023
  • KAKS22
    Karelia, Open UAS, All, Fall, 2022
  • TOP22_23
    Other Complimentary Studies Group Semester 2022-2023
  • KADS22SO
Small groups
  • Pienryhmä (schedulingGroup) 1
  • Pienryhmä (schedulingGroup) 2

Objective

- You learn how an artificial neural network works
- You learn how to use ready-made libraries for artificial neural networks
- You learn how to apply artificial neural networks to problem solving

Content

Artificial neural networks
Python libraries for neural networks

Teaching methods

Course grading is based on continuous evaluation through weekly assignments
- Assignments are graded from 0 to 5, and the course grade is the average grade from these assignments.
The minimum grade for passing the course is 1

- Lectures and exercises 35h
- Self-study 100h

Further information

Recommended course: Data analytics with Python, or
You master Python programming language, or
You have completed Programming essentials in Python course

Evaluation scale

H-5

Qualifications

- You master Python programming language, or
- You have completed Programming essentials in Python course
Recommended course: Data analytics with Python