== Software installation instructions ==
== Evening events ==
== Project descriptions ==
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[11:45 - 12:45] Introduction to School (Viviana and Zeljko)
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[14:00 - 16:30] Tutorial: Git, GitHub, and Notebooks (Paco)
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[8:30 - 9:45] Science drivers: the Milky Way and time domain (Zeljko)
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[10:15 - 11:30] Science drivers: Galaxies (Paco)
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[11:45 - 12:45] Science drivers: Quasars (Stefano Cristiani)
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[14:15 - 16:30] Tutorial: Accessing and Manipulating Data (Zeljko)
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[08:30 - 09:45] Intro to ML I (Paco)
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[10:15 - 11:30] Intro to ML II (Paco)
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[11:45 - 12:45] Decision Trees (Viviana)
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[14:15 - ] Tutorial: Globus + hdf5 (Paco)
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[ - 16:30] Tutorial: SQL and SDSS CasJobs (prepared by D. Baron) (Paco)
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[08:30 - 09:45] DT in code (Viviana)
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[10:15 - 11:30] Evaluating, Diagnosing, and Improving ML models (Viviana)
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[11:45 - 12.45] Exercise: DT and kNN (Viviana)
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[12:45 - 14.15] Lunch
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[14:15 - 16.00] Tutorial: “Accessing data from CAMELS simulations” (Paco)
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[19:00 - 20:00] Science drivers: InterGalactic Medium, Cosmology and Quasar Surveys (Stefano Cristiani)
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[08:30 - 09:45] Regression - Lecture notes (Viviana)
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[08:30 - 09:45] Regression - Notebook
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[10:15 - 11:30] Numerical simulations and AI (Paco)
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[11:45 - 12:45] Guest lecture by Adam Hincks: How to Measure the Oldest Light in the Universe and What it Tells us
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[12:45 - 14:15] Lunch
Afternoon: Projects Discussion (exact timing TBD)
- [19:00 - 20:00] Guest lecture by Giorgio Calderone: “QUBRICS: Selecting bright QSOs at high-z with Machine Learning techniques”.
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[08:30 - 09:45] Regularization - Lecture notes (Viviana)
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[08:30 - 09:45] ParamOp - Lecture notes (Viviana)
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[08:30 - 09:45] Param Op - Notebook
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[10:15 - 11:30] Working with neural networks (Paco)
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[11:45 - 12:45] Student talks I (Hanneke, Belen, Francesco; Chair: Ashod)
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[12:45 - 14.15] Lunch
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[19:00 - 20:00] Guest lecture by Maria Elena Monzani: Data-intensive searches for Dark Matter
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[08:30 - 09:45] Input data and distance measures - lecture (Dalya)
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[08:30 - 09:45] Input data and distance measures - Jupyter notebook (Dalya)
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[10:15 - 11:30] Ensemble methods (Viviana)
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[10:15 - 11:30] Photoz w/ RF Notebook
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[11:45 - 12:45] Student talks II (Bonny, Elodie, Rodrigo; Chair: Hanneke)
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[12:45 - 14.15] Lunch
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[19:00 - 20:00] Guest lecture by Richard DSouza: "Reconstructing the history of individual Milky-Way mass galaxies through cosmological simulations"
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[08:30 - 09:45] Density estimation - lecture (Dalya)
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[10:15 - 11:30] Boosting and Feature Importance (Viviana)
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[10:15 - 11:30] Boosting Notebook
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[11:45 - 12:45] High-z AGNs and their possible role on Reionization (ppt) (Andrea Grazian)
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[11:45 - 12:45] High-z AGNs and their possible role on Reionization (pdf) (Andrea Grazian)
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[08:30 - 09:45] Clustering - lecture (Dalya)
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[08:30 - 09:45] Clustering - Jupyter notebook (Dalya)
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[10:15-11:30] Dimensionality Reduction Part 1 (PCA) - lecture (Dalya)
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[10:15-11:30] Dimensionality Reduction Part 1 (PCA) - Jupyter notebook (Dalya)
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[08:30-09:45] Dimensionality Reduction Part 1 (PCA) - lecture (Dalya)
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[08:30-09:45] Dimensionality Reduction Part 1 (PCA) - Jupyter notebook (Dalya)
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[10:15-11:30] Dimensionality Reduction Part 2 (SOM, tSNE, UMAP) - lecture (Dalya)
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[10:15-11:30] Dimensionality Reduction Part 3 (Sequencer) - lecture (Dalya)
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[08:30-09:45] Dimensionality Reduction - example with the PHANGS dataset (Dalya)
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[10:15-11:30] Outlier Detection - lecture (Dalya)
- [8:30-9:45] Introduction to Deep Learning 1 (Marc)
- [10:15-11:30] Maximum Likelihood Method (Zeljko)
- [8:30-9:45] Introduction to Deep Learning 2 (Marc)
- [10:15-11:30] Introduction to Bayesian statistics (Zeljko)
- [8:30-9:45] Transformers1 (Marc)
- [10:15-11:30] Transformers2 (Marc)
- [8:30-9:45] Generative Models 1 (Marc)
- [10:15-11:30] Markov Chain Monte Carlo methods (Zeljko)
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[8:30-9:45] MCMC applications in Bayesian statistics (Zeljko)
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[10:15-11:30] Generative Models 2 (Marc)
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[11:45-12:30] Introduction to Project Management (Zeljko)