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• Select section General

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  General

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  • Select activity Course Description

    SCMP112 Numerical Computing with Python (Nov. 2019)

    Learn about research computing even with little programming experience. Covers programming in python, best practices and visualization. Some experience with python is required. The course will last 4 weeks with 2 lectures per week (mini/modular grad course).

    Teachers: Alexey Fedoseev, Ramses van Zon

    Start date: 5 Nov. 2019

    End date: 5 Dec. 2019
• Select section 1. Numerics

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  1. Numerics

  • Select activity Slides of Lecture 1

    

    Slides of Lecture 1 File

     Creative Commons Attribution 4.0 International License.
  • Select activity Notebook version of the lecture (with images)

    

    Notebook version of the lecture (with images) File ZIP

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    368.8 KB
  • Select activity Recording of Lecture 1

    

    Recording of Lecture 1 File

     Creative Commons Attribution-NoDerivatives 4.0 International License (CC BY-ND 4.0).
• Select section 2. Numpy and SciPy

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  2. Numpy and SciPy

  • Select activity Slides of lecture 2

    

    Slides of lecture 2 File

     Creative Commons Attribution 4.0 International License.
  • Select activity Notebook version of lecture 2 (with images)

    

    Notebook version of lecture 2 (with images) File ZIP

     Creative Commons Attribution 4.0 International License.

    10.8 KB
  • Select activity Recording of lecture 2

    

    Recording of lecture 2 File

     Creative Commons Attribution-NoDerivatives 4.0 International License (CC BY-ND 4.0).
• Select section 3. Solving Ordinary Differential Equations

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  3. Solving Ordinary Differential Equations

  • Select activity Slides of lecture 3

    

    Slides of lecture 3 File

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  • Select activity Recording of lecture 3

    

    Recording of lecture 3 File

     Creative Commons Attribution-NoDerivatives 4.0 International License (CC BY-ND 4.0).
• Select section 4. Visualization

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  4. Visualization

  • Select activity Slides of lecture 4

    

    Slides of lecture 4 File

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  • Select activity Notebook with examples

    

    Notebook with examples File IPYNB

     Creative Commons Attribution 4.0 International License.

    1.0 MB
  • Select activity Recording of lecture 4

    

    Recording of lecture 4 File

     Creative Commons Attribution-NoDerivatives 4.0 International License (CC BY-ND 4.0).
• Select section 5. Solving Partial Differential Equations

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  5. Solving Partial Differential Equations

  • Select activity Slides of lecture 5

    

    Slides of lecture 5 File

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  • Select activity Recording of lecture 5

    

    Recording of lecture 5 File

     Creative Commons Attribution-NoDerivatives 4.0 International License (CC BY-ND 4.0).
• Select section 6. Data and Input/Output

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  6. Data and Input/Output

  • Select activity Slides of lecture 6

    

    Slides of lecture 6 File

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  • Select activity Notebook version of the lecture

    

    Notebook version of the lecture File

     Creative Commons Attribution 4.0 International License.

    53.4 KB
  • Select activity Recording of lecture 6

    

    Recording of lecture 6 File

     Creative Commons Attribution-NoDerivatives 4.0 International License (CC BY-ND 4.0).
• Select section 7. Markov Chain Monte Carlo

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  7. Markov Chain Monte Carlo

  • Select activity Slides of lecture 7

    

    Slides of lecture 7 File

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  • Select activity Recording of lecture 7

    

    Recording of lecture 7 File

     Creative Commons Attribution-NoDerivatives 4.0 International License (CC BY-ND 4.0).
• Select section 8. Machine Learning

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  8. Machine Learning

  • Select activity Slides of lecture 8

    

    Slides of lecture 8 File

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  • Select activity Notebook with examples

    

    Notebook with examples File IPYNB

     Creative Commons Attribution 4.0 International License.

    78.0 KB
  • Select activity Recording of lecture 8

    

    Recording of lecture 8 File

     Creative Commons Attribution-NoDerivatives 4.0 International License (CC BY-ND 4.0).
• Select section Assignments

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  Assignments

  • Select activity Assignment 1

    

    Assignment 1 Page
  • Select activity Assignment 2

    

    Assignment 2 Page
  • Select activity Assignment 3

    

    Assignment 3 Page
  • Select activity Assignment 3 starting code heatimplicit.py

    

    Assignment 3 starting code heatimplicit.py File
  • Select activity Assignment 4

    

    Assignment 4 Page
• Select section Links

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  Links

  • Select activity Python web site

    

    Python web site URL
  • Select activity Numpy and SciPy documentation

    

    Numpy and SciPy documentation URL
  • Select activity Scientific Python Lectures

    

    Scientific Python Lectures URL
  • Select activity Anaconda Python distribution

    

    Anaconda Python distribution URL

    Very convenient on your own computer, less so on advanced research computing clusters.