Incubator Summer Academy - Next Level Data Science

Session

Course Package 8 (Helmholtz AI)

isa23_cp08

19 Sept 2023, 09:00

28. Introduction to Machine Learning (Part 1)

Alina Bazarova, Donatella Cea, Francesco Campi, Jiangtao Wang (FZ Jülich), Peter Steinbach (HZDR), Sebastian Starke (HZDR), Steve Schmerler (HZDR)

19/09/2023, 09:00

This course will introduce participants to the concepts of AI and Machine Learning, covering clustering and clasifications fundamentals as well as practical experience with standard methods for both techniques. Lastly, participants will gain an insight on best practises for evaluating a machine learning model's performance (ROC curve, FPR etc.)

29. Introduction to Machine Learning (Part 2)

Alina Bazarova, Donatella Cea, Francesco Campi, Jiangtao Wang (FZ Jülich), Peter Steinbach (HZDR), Sebastian Starke (HZDR), Steve Schmerler (HZDR)

20/09/2023, 09:00

This course will introduce participants to the concepts of AI and Machine Learning, covering clustering and clasifications fundamentals as well as practical experience with standard methods for both techniques. Lastly, participants will gain an insight on best practises for evaluating a machine learning model's performance (ROC curve, FPR etc.)

30. Introduction to Machine Learning (Part 3)

Alina Bazarova, Donatella Cea, Francesco Campi, Jiangtao Wang (FZ Jülich), Peter Steinbach (HZDR), Sebastian Starke (HZDR), Steve Schmerler (HZDR)

21/09/2023, 09:00

This course will introduce participants to the concepts of AI and Machine Learning, covering clustering and clasifications fundamentals as well as practical experience with standard methods for both techniques. Lastly, participants will gain an insight on best practises for evaluating a machine learning model's performance (ROC curve, FPR etc.)

31. Introduction to Machine Learning (Part 4)

Alina Bazarova, Donatella Cea, Francesco Campi, Jiangtao Wang (FZ Jülich), Peter Steinbach (HZDR), Sebastian Starke (HZDR), Steve Schmerler (HZDR)

22/09/2023, 09:00

This course will introduce participants to the concepts of AI and Machine Learning, covering clustering and clasifications fundamentals as well as practical experience with standard methods for both techniques. Lastly, participants will gain an insight on best practises for evaluating a machine learning model's performance (ROC curve, FPR etc.)