[ 536COSCPP1U20 ] UE Programming in Python I

Workload Education level Study areas Responsible person Hours per week Coordinating university
3 ECTS B1 - Bachelor's programme 1. year (*)Artificial Intelligence Sepp Hochreiter 2 hpw Johannes Kepler University Linz
Detailed information
Original study plan Bachelor's programme Artificial Intelligence 2020W
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. These exercises shall provide an introduction to Python. They 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.
  • 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 Online Assignments
Language English
Changing subject? No
Corresponding lecture in collaboration with 536COSCPP1V20: VL Programming in Python I (3 ECTS) equivalent to
536COSCPP1K19: KV Programming in Python I (6 ECTS)
On-site course
Maximum number of participants 35
Assignment procedure Direct assignment