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Programming with Python

Semester 3, 2025

Course Information

Form of Examination

Pass/fail with 75% required attendance, 2 assignments and a final presentation

Grades

The course is not graded and can only be passed/failed. Requirements:

  • Attendance: At least 75% required
  • Assignments: Two assignments must be submitted by the end of the quarter
  • Presentation: One brief presentation must be held at the end
  • Performance: At least 50% of assignment solutions must be correct
  • Collaboration: Groups of up to 3 students are permitted

All assignments are due by the end of the quarter (earlier submissions are highly encouraged). Each assignment addresses an algorithmic problem from the course that must be solved independently. More details will be provided at the introductory lecture.

Lecturer

Dr. Tobias Vlček Email: vlcek@beyondsimulations.com

Module Dates

You can find the lecture dates in your myKLU calendar.

Module Objectives

This module introduces programming with Python. Python is a modern and powerful programming language widely used in industry and academic projects. Students will learn how to find code-based solutions to basic and complex problems through many practical examples.

Upon completion of the course, students will:

  • Be able to implement solutions to complex problems in Python
  • Know basic concepts of programming and algorithms (loops, functions, object classes)
  • Be able to apply basic techniques of data manipulation and visualization
  • Be able to read and write code
  • Acquire experience working with core Python libraries (NumPy, Pandas, Matplotlib)
  • Know how to collaborate in a team to solve problems

Note: This course is specifically designed for business students. No prior programming knowledge or experience is required. The teaching format accommodates different skill levels so every student can maximize their learning.

Programming Environment

This course uses Python 3 as our primary programming language. We'll ensure everyone has a consistent development environment by walking through the setup process together during our first session.

What You Need: Please bring your laptop to class. We'll guide you through the installation process step-by-step for Windows, Mac, or Linux.

Module Structure

Part I: Introduction to Programming with Python

Introduction to basic programming concepts in Python, including syntax, data types, loops, functions, and object classes. Core Python libraries (NumPy and Pandas) will also be introduced.

Session Topic Content
I Welcome and Introduction Basics of Python syntax, variables, data types
II Control Structures for Your Code String methods, comparisons, conditional statements, loops
III Building Reusable Functions Functions, arguments, return values, scope, classes
IV Handling Data in More Than One Dimension Tuples, lists, sets, dictionaries, and basic I/O
V Handling Errors and Strings Exceptions, try-except blocks, debugging

Part II: Data Science with Python

Basic data science tools in Python covering data manipulation, descriptive and explorative analysis, and visualization, with an outlook on next steps in Python.

Session Topic Content
VI Using Modules and Packages Standard libraries, random numbers and their applications
VII NumPy for Scientific Computing Fast array operations with NumPy
VIII Pandas and AI Pandas for data manipulation and AI
IX Plotting Data Matplotlib with AI based on hands-on examples

Part III: Programming Projects

Students work on mini projects in Python applying their knowledge in groups. Each group presents results and receives feedback at semester's end.

Session Topic Content
X Your First Project I Choose your project that ties together course concepts
XI Your First Project II Progress your group project with assistance
XII Your First Project III Finalize your group project with your team
XIII Presentations and Discussion Present your group's work and share learnings

Lecture Materials

Lecture Slides: https://beyondsimulations.github.io/Introduction-to-Python/

Required Readings

Book Author Usage Type Pre-reading
Algorithmic Thinking, 2nd Edition: Unlock Your Programming Potential Zingaro, D. (2024) Entire Lecture Mandatory No
Think Python: How to Think Like a Computer Scientist (Third Edition) Downey, A. B. (2024) Entire Lecture Recommended No

Additional Readings

Programming Practice Platforms

  • Advent of Code: Daily programming challenges during Christmas time. Highly recommended for improving skills playfully.
  • Codewars: Platform to strengthen coding skills by solving challenges. Compete with others, see alternative solutions, and learn from others' code.
  • Tiny Python Projects: Interesting and fun projects to improve programming skills.

AI Tools

  • ChatGPT and Other AI Tools: Information about AI tool usage will be provided during the course.

This syllabus supports KLU's commitment to Inclusion, Diversity & Equality.