Courses & Teaching

A reverse-chronological list of courses I have lectured, co-taught, or delivered as guest teaching — most of them with what the students themselves wrote about it. The indented quotes are verbatim comments from the official course evaluations of that offering, reproduced exactly as students wrote them, typos included; the two teaching awards of Aalto’s Department of Computer Science listed below came out of the same evaluations.

Each entry is tagged with the host institution. Aalto codes follow the Aalto course catalogue; TU Wien codes (389.xxx) belong to the Institute of Telecommunications; IMC Krems courses run within the RAI MA (Master in Responsible AI / Applied AI) and UF BA (Bachelor in Unternehmensführung und Digitales Management) programmes. Open course materials (slides, notebooks, assignments) are linked per course and collected on GitHub.

Upcoming

• CS-E4740 Federated Learning D — Aalto University (spring 2027) · course repo

2026

• CS-E4740 Federated Learning D — Aalto University · materials

  “I think in general seeing federated learning problems as GTVmin problems really helps give more clarity on how to formulate them. Very good material and very well taught course.”

• MLR1ILV Machine Learning — IMC Krems (RAI MA, 1st semester, WS26/27)

• ETP1ILV Emerging Technologies und Programmierung — IMC Krems (UF BA, 1st semester, WS26/27)

• FML2ILV Federated Machine Learning — IMC Krems (RAI MA, 2nd semester, SS26) · materials

  “A well structured course with interesting assignments. I like the academical approach with the LateX paper assignments and the presentation, they are useful skills to learn.”

• CAI2VO Corporate AI — IMC Krems (UF BA, 2nd semester, SS26) · course repo

  “Großes Lob an den Dozenten- man merkt wie er für seine Sache brennt, diese Begeisterung steckt an!”

2025

• CS-A1155 Databases for Data Science — Aalto University

  “I really appreciate the positiveness and understanding of Alex Jung. He is without a doubt an amazing professor.”

• CS-E4740 Federated Learning D — Aalto University · materials

• MLR1ILV Machine Learning — IMC Krems (RAI MA, 1st semester, WS25/26)

  “Very intersting course with a top lecturer. Topics were extremely useful and understandable.”

2024

• CS-E4740 Federated Learning D — Aalto University · materials

2023

• CS-EJ3311 Deep Learning with Python D — Aalto University

• CS-EJ3211 Machine Learning with Python D — Aalto University
• CS-E4740 Federated Learning D — Aalto University · course repo

2022

• Award: 3rd Best Course of the Department of Computer Science, academic year 2021–2022 — Aalto University, for CS-EJ3211 Machine Learning with Python, in the category of big courses (feedback given by more than 50 students)

• CS-EJ3311 Deep Learning with Python D — Aalto University

  “The notebooks are made so brilliantly simple to understand that pretty much anyone with even a little coding experience can learn the basics of deep learning.”

  “The level of detail and instructions in JupyterHub was amazing. The best I have ever done.”

• CS-E407507 Special Course in Machine Learning and Data Science: Human-Centered Machine Learning — Aalto University (also delivered as the summer school “Human-Centered Machine Learning” of the European university alliance Unite!) · materials

  “Supportive and very pedagogical professor and also teaching assistant for practical part. Interesting topics and engaging lectures from guest lecturers too.”

• CS-EJ3211 Machine Learning with Python D — Aalto University · notebooks

  “This has really been the best course with coding as a tool for learning so far.”

• CS-E407508 Special Course in Machine Learning and Data Science: Networked Federated Learning — Aalto University

• CS-C3240 Machine Learning D — Aalto University · materials
• Foundations of Machine Learning and Deep Learning & Advanced Topics — guest course, Mid Sweden University, Sundsvall (SE): a two-day course (regularization, semi-supervised and transfer learning, clustering, PCA) with hands-on Python (JupyterLab) exercises at the PLENOPTIMA Training School 2 “Machine and Deep Learning for Plenoptics” (19–23 Sep 2022), part of the EU Horizon 2020 MSCA European Joint Doctorate network PLENOPTIMA · slides

2021

• CS-EJ3311 Deep Learning with Python D — Aalto University

• CS-EJ3211 Machine Learning with Python D — Aalto University

• CS-C3240 Machine Learning D — Aalto University

  “Alex Jung is a great teacher of machine learning. I learned machine learning in a very interesting and comprehensive manner.”

2020

• CS-EJ3311 Deep Learning with Python D — Aalto University

• CS-EJ3211 Machine Learning with Python D — Aalto University

• CS-E4070 Special Course in Machine Learning and Data Science D — Aalto University

• Machine Learning — guest course, Integrify, Helsinki (FI): main teacher for the Machine Learning program of a Finnish training provider upskilling immigrants and international talent for careers in tech (2019–2020)

2019

• CS-EJ3211 Machine Learning with Python D — Aalto University · notebooks

• CS-EV Course with Varying Content — Aalto University

2018

• Award: Teacher of the Year 2018 of the Department of Computer Science — Aalto University, awarded on the basis of student nominations

  “The methodology he uses in his course is great. He really cares about his teaching inviting people to give us talks and other special events/seminars. He’s a person who is always there to help you.”

• CS-E3210 Machine Learning: Basic Principles D — Aalto University · textbook

  “This course was one of the best courses I have taken in Aalto.”

  “Drawing lectures are amazing. Great way to show the lecturers mastery to the subject! A joy to attend.”

  “The exercises are well thought and developed. I like how the lecturer always starts explanations from examples and in general he is an excellent speaker and knows how to transfer his knowledge.”

  “It was perfect course for beginner to get motivated. Thank you so much Alex.”

• CS-E4800 Artificial Intelligence D — Aalto University

  “Alex did a good job with his drawings in the lectures, they were easy to follow and enlightning.”

2017

• CS-E3210 Machine Learning: Basic Principles D — Aalto University · textbook

  “Alex Jung was an excellent lecturer, the best lecturer I’ve heard in a long time.”

  “The technical quality of the assignments was excellent. Also, I wish other lectures as Aalto were as positive and as motivated as Alex.”

  “It was possible to take the course without physical attendace. On the other hand lecturer was so good that I really wanted and did participated almost every lecture.”

  “I really admire the knowledge that Alexander Jung showed us at the lecture, he seems to be a real expert”

• CS-E4020 Special Course in Machine Learning and Data Science II D — Aalto University

  “A very nice and, for me, novel approach to convex optimization using fixed-point iterative algorithms.”

2016

• CS-E3210 Machine Learning: Basic Principles D — Aalto University · textbook

  “Alex is the best professor I’ve encountered in Aalto university and one of the best ones in general. Really really good, doing his absolutely best to help student understand.”

  “Alexander’s lectures were very good, interactive and inspirational ++”

• T-61.6020 Special Course in Computer and Information Science II D — Aalto University

  “Alex taught everything in detail, very clear to understand”

2015

• T-61.3050 Machine Learning: Basic Principles — Aalto University · textbook

  “Especially good on the course was the high pedagogical level of lectures by Alex Jung! Thank you for that!”

  “The term project and practical approach. Excellent slides. Professor Alex Jung gave great lectures.”

• 389.186 Signal Processing for Big Data — TU Wien (Institute of Telecommunications; co-taught with N. Görtz and G. Tauböck)

2014

• 389.178 Compressed Sensing — TU Wien (Institute of Telecommunications; co-taught with N. Görtz and G. Tauböck)