Python is a multi-purpose, flexible, and powerful programming language, with a broad diversity of relevant jobs in many fields, especially data science. It is a great language for beginners because it is concise and easy to read. This course will introduce the learner to the basics of the python programming ecosystem and how skills of programming and other features in python can be used in analysis of various data.

A data analyst can use programming tools to explore and process large amounts of complex data and find relevant information or pattern from this data. They can extract valuable information from chaotic data. In order to be an outstanding data analyst, they need to also have programming skills in addition to their own domain. Python is a programming language used by many data scientists to clean data, make visualizations and build decision or prediction models or perform classification and clustering. This course provides a beginner-friendly introduction to Python with a special focus on data analysis. Practice through lab exercises, and you will be ready to create your first python program in your own domain.

Program

Period 1: Python Crash Course
Week 1: Introduction to Python
Week 2: Conditionals and Control Flow
Week 3: Loops and Iteration
Week 4: Functions
Week 5: Lists and Tuples
Week 6: Dictionaries and Sets
Week 7: Object Oriented Programming (OOP) Concepts
Week 8: Modules and Packages

OP2: Applied Data Science
Week 1: Introduction to Jupyter Notebook, NumPy, and Pandas
Week 2: Working with DataFrames
Week 3: Data Manipulation and Preparation with Pandas
Week 4: Data Visualization with Matplotlib and Seaborn
Week 5: Machine Learning Fundamentals
Week 6: Supervised Learning
Week 7: Model Training, Evaluation, and Validatio

Learning goals
Upon completion of this course, students will be able to:

• Understand, develop, and apply the fundamentals of programming in the Python environment: data types and variables, expressions, program flow, and decision statements (such as branching and looping), more complex data structures (such as list, tuple, set, and dictionary), functions, files, modules, libraries, etc.
• Apply various programming skills and tools to data analysis and processing, including importing, cleaning, manipulating, and visualizing data. Create machine learning models and export information from data using the models.
• Create a project in their own practical domain to demonstrate their ability in programming skills and applied data science techniques and tools in Python.

1. you have successfully completed your internship. 
2. You have obtained a minimum of 90 credit points from the main phase of your study programme. 

This course is designed for students of all backgrounds who want to apply programming skills and functions to projects in their own fields. However, this course is NOT designed for computer science students. Or any program that includes a programming course in
its curriculum. For example, students in programs such as Applied Data Science & Artificial Intelligence, Creative Media and Game Technologies, Informatica, and Technical Informatica can't take this course.

Attention! For this minor, there is a maximum number of participants combined with a lottery and an earlier closing date. If you want to participate in the lottery, please register before 09:00 AM - 2th May 2025 at the latest.

Evaluation will be based on assignments without exams.

These are the key points of the course evaluation:

1. For each OP, students will have:

• Weekly assignments.
• A final assignment at the end of the period.

2. Each period will be evaluated separately based on the overall evaluation of the weekly and final assignments.

3. Students must pass both periods to pass the course.

GENERAL

• For this course a laptop is required.
• There is no attendance requirement.
• Students will work in groups.
• Teaching materials will be provided in the form of slides by the instructor.
• For more information, contact the course coordinator.

Minor Choice Week | 2–5 March 2026

Online minor information sessions
Attend an online information session for this minor! View the programme and register here.

Minor fair
This minor will be present at the minor fair. Will you join us? View the programme and register here.

Date: Thursday, 5 March 2026
Time: 4:00–7:30 p.m.
Location: Kralingse Zoom

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APPLICATION PROCESS (KOM)

Are you a student from another educational institution and would you like to follow a minor at Rotterdam University of Applied Sciences? If so, you must apply in two steps:

Step 1

• Register for the minor of your choice via the blue Apply button. You can find this button at the top right of the minor’s page.
• Download the learning agreement and complete it.
• Submit this learning agreement to the examination board of your study programme.

Once the examination board has granted approval, register for the minor in Step 2 no later than 01-07-2025 at 9:00 a.m.

Step 2
After approval, register via OSIRIS Application of Rotterdam University of Applied Sciences using the link below (first create an account).
https://osiris.hr.nl/osiris_aanmeld_hrprd/Welkom.do?proces=KOM2609&opleiding=MINOR-CMI-VT 00

Part of the application process is uploading the following documents:

• The learning agreement, signed by you and by your institution;
• A scan or photo of your passport or ID card.

You will be informed by Rotterdam University of Applied Sciences whether your application has been approved.

In OSIRIS Application, you must also upload the Proof of Paid Tuition Fee (BBC) for the academic year in which you wish to follow the minor. This can be done from 01 May 2026 onwards. You can request the BBC from your institution after you have signed or issued an authorization for the payment of the tuition fee for the relevant academic year. You may also choose the option for your institution to send the BBC directly to collegegeld@hr.nl.

You will receive a notification from Rotterdam University of Applied Sciences once your application has been approved.