To gain ability to use Python programming language. To gain the ability to use artificial intelligence features.
20
Contribution of the Course to Professional Development
To be able to write general purpose program with Python programming language.
21
Learning Outcomes:
1
Gain knowledge on Python programming;
2
Gain knowledge concerning with installation and tools;
3
Gain knowledge concerning with interfaces and libraries;
22
Course Content:
Week
Theoretical
Practical
1
Introduction
2
Interfaces and assistant packages
3
Tuples, lists
4
Dictionary, set
5
Functions
6
Modules
7
Wrap up
8
Class
9
Objects
10
Inheritance
11
Iterator, Generator
12
Machine Learning
13
Machine Learning
14
Wrap up
23
Textbooks, References and/or Other Materials:
The Python Tutorial Think Python, How to Think Like a Computer Scientist Allen Downey Intro to Python for Computer Science and Data Science Paul J. Deitel, Harvey M. Deitel
24
Assesment
TERM LEARNING ACTIVITIES
NUMBER
PERCENT
Midterm Exam
1
40
Quiz
0
0
Homeworks, Performances
0
0
Final Exam
1
60
Total
2
100
Contribution of Term (Year) Learning Activities to Success Grade
40
Contribution of Final Exam to Success Grade
60
Total
100
Measurement and Evaluation Techniques Used in the Course
Classical problem-solving ability will be measured in midterm and final exams.
Information
25
ECTS / WORK LOAD TABLE
Activites
NUMBER
TIME [Hour]
Total WorkLoad [Hour]
Theoretical
14
3
42
Practicals/Labs
0
0
0
Self Study and Preparation
14
3
42
Homeworks, Performances
0
0
0
Projects
0
0
0
Field Studies
0
0
0
Midtermexams
1
30
30
Others
0
0
0
Final Exams
1
36
36
Total WorkLoad
180
Total workload/ 30 hr
5
ECTS Credit of the Course
5
26
CONTRIBUTION OF LEARNING OUTCOMES TO PROGRAMME QUALIFICATIONS
