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- Intro of the course - 05/04/2024 - slides
- Lecture 1: Probability, Bayes theorem, random variables, probability density functions, expectation values, correlation and pdf transformations - 05/04/2024 - slides 1
- Lecture 2: Python intro, variables, functions, classes, numpy and pandas libraries, plotting - 12/04/2024 - slides 2 - notebooks: notebook_01, binder,
- Lecture 3: Pdf catalogue, Python SciPy library, Visualizing data, histograms - 19/04/2024 - slides 3 - notebooks: notebook_02
- Lecture 4a: Montecarlo method, random numbers with Python - 26/04/2024- slides 4 - notebooks: notebook_03
- Lecture 4b: Montecarlo method, random numbers with Python - 10/05/2024 - slides 4 - notebooks: notebook_03
- Lecture 5: Parameter estimation - 24/04/2024 - slides 5
- Lecture 6: Curve Fitting - 21/06/2024 - slides 6 - notebooks: notebook_04
- Lecture 7: Hypotesis test - 28/06/2024 - slides -
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