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These lectures are part of the training offer (link) of the PhD course in Science of Matter and Nanomaterials at the University of Roma Tre.
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2024 academic year
This course is structured in frontal lessons and practical example lessons using Python.
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The lecture calendar is available here.
The course material will be uploaded before each lesson here:
- Intro of the course - 2705/0304/2023 2024 - slides
- Lecture 1: Probability, Bayes theorem, random variables, probability density functions, expectation values, correlation and pdf transformations - 2705/0304/2023 2024 - slides 1
- Lecture 2: pdf catalogue, Montecarlo method - 31/03/2023 - slides 2a, slides 2bLecture 3: Python intro, variables, functions, classes, numpy and pandas libraries, plotting - 0312/04/2023 (recording) 2024 - slides 2 - notebooks:nbviewer notebook_01, binder, .zipLecture 4: Generating random variables with Python - 14/04/2023 (recording) - notebooks: nbviewer, binder, .zip,
- 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 and Maximum Likelihood Estimators - 1724/04/2023 2024 - slides 5
- Lecture 6: Confidence intervals, Curve fit, Least square method Curve Fitting - 21/06/2024 - slides 6 - notebooks: notebook_04/2023 - slide 6a, slide 6b
- Lecture 7: Hypotesis test - 28/06/2024 - slides -
- Lecture 8: Classification - 12/07/2024 - slides -
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