Python for Scientists and Engineers

Python for Scientists and Engineers

Python for Scientists and Engineers
Python for Scientists and Engineers

Python for Scientists and Engineers

If you're a scientist or an engineer interested in learning scientific computing, this is the place to start.

In this course, you'll learn to write your own useful code to perform impactful scientific computations. Along the way, your understanding will be tested with periodic quizzes and exercises.

Topics covered in this course include arrays, plotting, linear equations, symbolic computation, scientific algorithms, and random variables. 


You’ll also be exposed to popular Python packages like NumPy, Matplotlib, SciPy, and others.

In the last part of the course, the application section will test your ability to recall and apply the tools you have studied into newly learned scientific concepts.

At the end of this course, you'll be equipped with the tools necessary for everyday scientific computation.

Contents

1. Introduction

  • Introduction
  • About This Course
2. Python Refresher
  • Data Types and Variables
  • Operators
  • Conditional Statements
  • Loops
  • Functions
  • Lambdas
  • Lists
  • Tuples and Dictionaries
  • Using Python Packages
  • Quiz 1!
  • Exercise: Check Sum
  • Solution Review: Check Sum
3. Arrays
  • Introduction
  • Vectors
  • Multidimensional Arrays
  • Quiz 2!
  • Indexing Arrays
  • Array Operations
  • Data Processing
  • Smart Array Programming
  • Quiz 3!
  • Exercise: Accessing 2-Dimensional Arrays
  • Solution Review: Accessing 2-Dimensional Arrays
  • Exercise: Using Conditions on Arrays
  • Solution Review: Using Conditions on Arrays
4. Plotting
  • Basic Plotting
  • Important Note!
  • Plotting Multiple Curves
  • Setting Up the Axes
  • Gallery of Graphs
  • 3-D Plots
  • Quiz 4!
  • Exercise: Plotting Temperatures
  • Solution Review: Plotting Temperatures
  • Exercise: Plotting Torus
  • Solution Review: Plotting Torus
5. Systems of Linear Equations
  • Building and Solving Linear Equations
  • Eigenvalues and Eigenvectors
  • Matrix Operations
  • Sparse Matrices
  • Quiz 5!
  • Exercise: Fitting a Wave
  • Solution Review: Fitting a Wave
6. Symbolic Computation
  • Introduction
  • Symbols and Complex Numbers
  • Numerical Evaluation
  • Algebraic Manipulation
  • Quiz 6!
  • Differentiation
  • Integration
  • Limits
  • Quiz 7!
  • Series Expansion
  • Solving Equations
  • Ordinary Differential Equations
  • Quiz 8!
  • Exercise: Integrating Complex Functions
  • Solution Review: Integrating Complex Functions
  • Exercise: Solve a Differential Equation
  • Solution Review: Solve a Differential Equation
7. Scientific Algorithms
  • Introduction
  • Numerical Integration
  • Interpolation
  • Quiz 9!
  • Polynomial Fitting
  • Curve Fitting
  • Optimization
  • Fourier Transforms
  • Quiz 10!
  • Exercise: Triple Integral Over a Bounded Region
  • Solution Review: Triple Integral Over a Bounded Region
  • Exercise: Parameters of an FID Signal
  • Solution Review: Parameters of an FID Signal
8. Random Variables
  • Random Numbers
  • Flipping Coins
  • Bernoulli Variable
  • Normal Continuous Random Variables
  • Histograms and Probability Density Function
  • Percentiles
  • Quiz 11!
  • Exercise: Predicting Election Results
  • Solution Review: Predicting Election Results
9. Applications
  • Introduction
  • Preview: Setting Up an Optical System
  • Exercise: Setting Up an Optical System
  • Solution Review: Setting Up an Optical System
  • Preview: Transfer Functions
  • Exercise: Transfer Functions
  • Solution Review: Transfer Functions
  • Preview: Harmonographs
  • Exercise: Harmonographs
  • Solution Review: Harmonographs
10. Conclusion
  • Last Thoughts
  • Where to Go from Here
11. Appendix
  • Files I/O
  • LaTeX Formatting
https://www.educative.io/courses/python-for-scientists-and-engineers?aff=xDzJ

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