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Python For Engineers and Professionals

Intro to Numeric Computing with Python

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  • Basics and Plotting — Notebook 1 — Video
  • Arrays — Notebook 2 — Video
  • For loops and If/Else statements — Notebook 3 — Video
  • Functions — Notebook 4 — Video
  • Finding the Zeros of a Function — Notebook 5
  • Systems of linear equations — Notebook 6
  • Bugs — Notebook 7
  • Pandas and Time Series — Notebook 8 — Video (Python 2)
  • Discrete Random Variables — Notebook 9 — Video
  • Continuous Random Variables — Notebook 10 — Video
  • Distribution of the Mean and Hypothesis Tests Theorem — Notebook 11 — Video (Python 2)
  • Object oriented programming — Notebook 12 — Video (Python 2)
  • Regression I — Notebook 13

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Python Plotting

Intro to Python and Programming - Yuov Ram

Link Another Intro

  • Recitation 1: variables, operators, flow control
  • Recitation 2: input, Collatz Conjecture, lists, functions
  • Recitation 3: diviors, timing operations, binary system, base conversion, Python's memory model
  • Recitation 4: time complexity, Big O notation, primality testing, Diffie-Hellman key exchange
  • Recitation 5: object-oriented programming, recursion
  • Recitation 6: recursion, quicksort
  • Recitation 7: lambda expression, high-order functions, Matrix class, file handling
  • Recitation 8: hash functions, hash tables, finding repeating substrings
  • Recitation 9: linked list, iterators, generators
  • Recitation 10: Rabin-Karp algorithm for string matching
  • Recitation 11: Huffman code
  • Recitation 12: LZ compression
  • Recitation 13: image processing, denoising algorithms
  • Recitation 14: error detection and correction

Numpy Guru:

[HUHA] Applied Python: A course in numerical methods with Python for engineers and scientists:

Currently 5 learning modules, with student assignments

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  • The phugoid model of glider flight.
  • Space and Time—Introduction to finite-difference solutions of PDEs.
  • Riding the wave: convection problems.
  • Spreading out: diffusion problems.
  • Relax and hold steady: elliptic problems. Laplace and Poisson equations

Data Science with Python - Yuov Ram

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  • Numerical Python with NumPy: notebook | solution
  • Plotting with Matplotlib: notebook | solution
  • Data analysis with Pandas and Seaborn: notebook | solution
  • Machine learning with Scikit-learn: notebook | exercise: linear model | solution | solution: linear model | exercise: logistic model | solution: logistic model

Dealing with more Data

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  • EngComp(1-4) - data oriented problems

Simulations and Advanced Computing

Advanced Scientific Computing : Monte Carlo and Stochastic optimization

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Digital Signal Processing

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