Fundamental programming for data analytics, 6 credits
Grundläggande programmering för dataanalys, 6 hp
TNK128
Main field of study
Computer Science and EngineeringCourse level
First cycleCourse type
Programme courseExaminer
Nils BreyerDirector of studies or equivalent
Erik BergfeldtEducation components
Preliminary scheduled hours: 0 hRecommended self-study hours: 160 h
Available for exchange students
YesCourse offered for | Semester | Period | Timetable module | Language | Campus | ECV | |
---|---|---|---|---|---|---|---|
6MTSL | Intelligent Transport Systems and Logistics, Master's Programme | 1 (Autumn 2023) | 1 | 1 | English | Norrköping | C |
6MDIB | Master's Programme in Digital Construction Management | 1 (Autumn 2023) | 1 | 1 | English | Norrköping | C |
Main field of study
Computer Science and EngineeringCourse level
First cycleAdvancement level
G1XCourse offered for
- Master's Programme in Intelligent Transport Systems and Logistics
- Master's Programme in Digital Construction Management
Prerequisites
Admission requirements for master level studies
Intended learning outcomes
In this course, you will learn how to use programming for problem solving and analysis of data.
After completing the course, the student should be able to:
- Write scripts for data analysis using Python
- Use basic data structures for problem solving in Python
- Apply tools available in some commonly used Python packages
- Generalize programming skills in Python to other script languages, specifically Matlab
Course content
- Introduction to different types of programming paradigms and languages
- Python basics: programming environment and documentation, program flow, variables, comments, numerical operators, loops, conditional statements
- Python data structures and looping techniques: tuples, lists, dictionaries, sets, iterators, and generators
- Python standard libraries and essential third-party packages for data manipulation, numerical computing, and visualization
- Debugging of code
- Data retrieval from various sources, such as json files, csv files, html files, XML files, databases or APIs
- Introduction to Matlab programming and toolboxes
Teaching and working methods
Lectures, tutorials and labs
Examination
DAT1 | Computer exam Python | 3 credits | U, 3, 4, 5 |
LAB1 | Laboratory work in Python | 1.5 credits | U, G |
LAB2 | Laboratory work in Matlab | 1.5 credits | U, G |
Grades for examination modules are decided in accordance with the assessment criteria presented at the start of the course.
Grades
Four-grade scale, LiU, U, 3, 4, 5Department
Institutionen för teknik och naturvetenskapCode | Name | Scope | Grading scale |
---|---|---|---|
DAT1 | Computer exam Python | 3 credits | U, 3, 4, 5 |
LAB1 | Laboratory work in Python | 1.5 credits | U, G |
LAB2 | Laboratory work in Matlab | 1.5 credits | U, G |
Grades for examination modules are decided in accordance with the assessment criteria presented at the start of the course.
Note: The course matrix might contain more information in Swedish.
I | U | A | Modules | Comment | ||
---|---|---|---|---|---|---|
1. DISCIPLINARY KNOWLEDGE AND REASONING | ||||||
1.1 Knowledge of underlying mathematics and science (G1X level) |
|
|
|
|||
1.2 Fundamental engineering knowledge (G1X level) |
|
|
|
|||
1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level) |
|
|
|
|||
1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level) |
|
|
|
|||
1.5 Insight into current research and development work |
|
|
|
|||
2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES | ||||||
2.1 Analytical reasoning and problem solving |
|
|
|
|||
2.2 Experimentation, investigation, and knowledge discovery |
|
|
|
|||
2.3 System thinking |
|
|
|
|||
2.4 Attitudes, thought, and learning |
|
|
|
|||
2.5 Ethics, equity, and other responsibilities |
|
|
|
|||
3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION | ||||||
3.1 Teamwork |
|
|
|
|||
3.2 Communications |
|
|
|
|||
3.3 Communication in foreign languages |
|
|
|
|||
4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT | ||||||
4.1 External, societal, and environmental context |
|
|
|
|||
4.2 Enterprise and business context |
|
|
|
|||
4.3 Conceiving, system engineering and management |
|
|
|
|||
4.4 Designing |
|
|
|
|||
4.5 Implementing |
|
|
|
|||
4.6 Operating |
|
|
|
|||
5. PLANNING, EXECUTION AND PRESENTATION OF RESEARCH DEVELOPMENT PROJECTS WITH RESPECT TO SCIENTIFIC AND SOCIETAL NEEDS AND REQUIREMENTS | ||||||
5.1 Societal conditions, including economic, social, and ecological aspects of sustainable development for knowledge development |
|
|
|
|||
5.2 Economic conditions for knowledge development |
|
|
|
|||
5.3 Identification of needs, structuring and planning of research or development projects |
|
|
|
|||
5.4 Execution of research or development projects |
|
|
|
|||
5.5 Presentation and evaluation of research or development projects |
|
|
|
This tab contains public material from the course room in Lisam. The information published here is not legally binding, such material can be found under the other tabs on this page.
There are no files available for this course.