To foster community spirit, we have planned several social events throughout the program, including a Welcome Party, a visit to the Planetarium, and a day trip to the picturesque mountains of Beskydy.
Saturday, 17 August 2024
Arrival of students and check-in to the hotel
Sunday, 18 August 2024
Summer School Welcome Event at IT4Innovations
| 12:00 | Lunch |
| 13:30 | Introduction of the school program, practical information |
| 14:00 | Introduction of the organizers |
| --> IT4I | |
| --> VSC | |
| --> MathWorks | |
| --> EUMaster4HPC | |
| 15:00 | Coffee break |
| 15:30 | Guided tours around IT4I’s infrastructure |
| 16:30 | Teambuilding activities |
| 18:00 | Welcome reception |
| 21:00 | End of the day |
Monday, 19 August 2024
| 09:00 | Accessing and using IT4I clusters |
| --> First login | |
| --> How to get your data to the cluster | |
| --> How to log in to the cluster and prepare a computation environment | |
| --> How to submit computational jobs | |
| 10:30 | Coffee break |
| 11:00 | Introduction to Data Science |
| 12:30 | Lunch break |
| 13:30 | Coding challenge part 1 |
| 15:00 | Coffee break |
| 15:30 | Coding challenge part 2 |
| 17:00 | End of the day |
Tuesday, 20 August 2024
| 09:00 | Introduction to R |
| --> What is R and when to consider using it? | |
| --> Basic data types | |
| --> Programming styles in R | |
| --> Very short introduction into tidyverse | |
| 10:30 | Coffee break |
| 10:45 | Exploratory Data Analysis with R |
| --> How to get basic understanding of data | |
| --> Explore and handle missing values and outliers | |
| --> Clean up messy data | |
| --> Visualization of basic relationships | |
| 12:15 | Lunch break |
| 13:15 | Modelling with R |
| --> Introduction to modelling with tidy models packages | |
| --> Creation of basic ML pipeline | |
| --> An end-to-end example with XGBoost | |
| 15:00 | Coffee break |
| 15:15 | Parallelization in R |
| --> Local machine parallelization | |
| --> Differences of parallelization on Windows and UNIX OS | |
| --> Multi-node parallelization | |
| --> Simple multi-node example in data science workflow | |
| 17:00 | End of the day |
Wednesday, 21 August 2024
| 09:00 | Challenge Reports: 1st cohort of EUMaster4HPC students |
| 10:30 | Coffee break |
| 10:45 | Dask, Numba, Ray: Parallelise the lazy way |
| 11:30 | Fast, faster, NumPy: Why is the popular library hard to beat? |
| 12:00 | Numerical computations on a GPU: Which tool does the best job? |
| 12:30 | Lunch break |
| 13:30 | Data analysis in Python: Pandas, Polars and the rest of the zoo |
| 15:00 | Coffee break |
| 15:15 | Data visualization: Insightful and pretty?! |
| 16:30 | Quiz & Recap |
| 17:30 | Leaving from the hotel to the Planetarium |
| 17:30 | Social event at Planetarium |
Thursday, 22 August 2024
| 09:00 | ML intro: Welcome to weight watching |
| 09:30 | Scikit-Learn: Get to know a living fossil |
| 09:45 | Regression vs Classification: What’s your problem? |
| 10:00 | Data pre-processing: Visualize, clean, transform |
| 10:30 | Coffee break |
| 10:45 | Prominent ML algorithms: SVMs, Decision Trees, K-nearest neighbors & ensemble methods |
| 11:00 | Evaluation: Which model performed best? |
| 11:30 | Hyperparameters: Twiddle the knobs and dials |
| 12:00 | Scaling Scikit-Learn: Dask and RAPIDS to the rescue |
| 12:30 | Lunch break |
| 13:30 | Neural Networks: Dive in at the deep (learning) end |
| 14:15 | Tensorflow & Keras: The easy way to become an architect |
| 15:00 | Coffee break |
| 15:15 | Convolutional Neural Networks: Give your computer a vision |
| 16:15 | Distributed Training: Sharing the burden |
| 16:45 | Outlook on Transformers: Welcome to the future |
| 17:00 | End of the day |
Friday, 23 August 2024
| 09:00 | Writing fast and efficient MATLAB code |
| --> 1000x speed-up: Exploring the MATLAB performance landscape | |
| --> Code profiler and best practices | |
| --> Parallelizing MATLAB code: From desktop to HPC and cloud | |
| --> GPU computing in MATLAB | |
| 10:30 | Coffee break |
| 10:45 | Big Data Analysis with MATLAB |
| --> Reading big data, using parquet files | |
| --> Datatypes for big data (datastores, tall arrays) | |
| --> Downstream analysis of big data: “needle in the haystack”-analysis, “for each”-analysis, “across all”-analysis | |
| --> Interoperability | |
| 12:15 | Lunch break |
| 13:15 | onwards hands-on work |
| --> Choose a project that fits your interests. Projects will introduce additional MATLAB functionality in the areas of large scale HPC, Deep Learning, Image Processing, and Signal Analysis. | |
| 15:00 | Coffee break |
| 15:15 | From coding to cluster – scaling up MATLAB on HPC |
| --> Sending jobs to a remote HPC cluster from the MATLAB environment | |
| --> Training AI model on a GPU without learning CUDA | |
| --> Multi-node parallelization | |
| --> NEW! MATLAB and Quantum Computing | |
| 17:00 | End of the day |
Saturday, 24 August 2024
Trip to Pustevny
Sunnday, 25 August 2024
Departure
