[ 536COSCPP1K19 ] KV Programming in Python I

Workload Education level Study areas Responsible person Hours per week Coordinating university
6 ECTS B1 - Bachelor's programme 1. year Computer Science Sepp Hochreiter 4 hpw Johannes Kepler University Linz
Detailed information
Original study plan Bachelor's programme Artificial Intelligence 2019W
Objectives Python (, one of the most commonly used programming languages in machine learning and AI, is a powerful and versatile programming language that allows for fast prototyping in simple scripts up to complex large-scale software development. This lecture shall provide an introduction to Python. It will start with the basics of programming and continue on to solving realistic tasks. After completing the course, students will be able to use Python in order to implement basic scientific applications in the field machine learning. Lecture and lecture materials are partly interactively.
  • Introduction to programming (crash-course: program execution, CPU, GPU, memory, Pointers)
  • Setting up the working environment
    • Usage of Python Interpreter
    • Usage of PyCharm Editor
    • "Hello World" program
    • Debugging Code
  • General Python syntax/style
    • comments, syntax, style
    • data types (variables, strings, lists, dictionaries, ...)
    • conditions
    • loops
    • list comprehensions
    • exceptions
    • functions
    • regular expressions
    • classes
  • Introduction to modules commonly used in machine learning:
    • os/sys (Python as pseudo shell-script)
    • Matlpotlib/Pyplot (Plotting in Python)
    • Numpy (efficient computation in Python)
    • h5py (storing and accessing large data using hdf5 in Python)
    • Multiprocessing (subprocesses in Python)
    • Numba (compiling and speeding up Python programs)
    • Preview on Tensorflow/Pytorch (GPU computations in Python)
Criteria for evaluation
Language English
Changing subject? No
On-site course
Maximum number of participants -
Assignment procedure Direct assignment