Please note: this minor has a selection procedure and an earlier closing date. Read the Entry Requirements carefully if you want to register for this minor.

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 INTRODUCTION TO PYTHON 1
Week2: 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 MODULES

Period 2: 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
Week 5: Machine Learning Fundamentals
Week 6: Supervised Learning
Week 7: Unsupervised Learning
Week 8: Model Training, Evaluation, and Validation

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 intended for students of any background who want to apply programming skills and functions to projects in their own fields. This course is NOT intended for computer science students.

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 - 6th May 2024 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.