Master Math by Coding in Python

Master Math by Coding in Python

by Codestars by Rob Percival, Mike X Cohen
Released August 2021
Publisher(s): Packt Publishing
ISBN: 9781801074537

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Video description

Many people don’t know that Python is a really powerful tool for learning math. Sure, you can use Python as a simple calculator, but did you know that Python can help you learn more advanced topics in algebra, calculus, and matrix analysis? That’s exactly what you’ll learn in this course.

The glaring question would be: if you don’t know anything about Python, then how will you code?

Don’t worry, this course is aimed at complete beginners; the instructor will take you through every step of the code. You don’t need to know anything about Python, although it’s useful if you already have some programming experience.

Even if you are not at all good at math, you will be amazed at how much better you can learn math using Python as a tool to help with your courses or your independent study. And that’s exactly the point of this course: Python programming as a tool to learn mathematics. This course is designed to be the perfect addition to any other math course or textbook that you are going through.

A lot of hands-on practical exercises come with this course, each video has at least one hands-on coding/math exercise and each section ends with “bug hunts“ where you get to find and fix math-coding errors.

By the end of the course, you will be able to understand very complex mathematical concepts with a bit of coding in Python.

What You Will Learn

  • Confidence in learning math using Python
  • Formatting beautiful equations in LaTeX
  • Integrating Python, Markdown, and LaTeX
  • Python programming and data visualization
  • Learn complex math concepts like calculus, trigonometry, and much more
  • Solving for “x” to computing integrals to finding eigenvalues

Audience

This course is for absolute beginners and individuals who are looking to use computers as a learning tool and developers who want to improve their math skills. If you are in middle/high school, university, or are returning to math as an independent learner or a data professional who wants to brush up on math and Python skills, you will definitely benefit from this course. If you are bored and looking for a fun intellectual challenge, then go for it.

You need not have any prior experience or knowledge in coding; just be ready with your learning mindset at the highest level.

About The Authors

Codestars By Rob Percival: Codestars, by Rob Percival, is a revolutionary online learning platform on a mission to transform the way people learn to code. With a focus on simplicity, logic, and fun, Rob has empowered over half a million students through his courses.

Recognizing the need for diverse and comprehensive learning experiences, Rob established Codestars as a collaborative effort. Codestars provides learners of all ages and proficiency levels with the tools and knowledge needed to build functional websites and apps. By making coding accessible and enjoyable, Codestars aims to simplify the learning journey and unlock the potential of aspiring coders worldwide.

Mike X Cohen: Mike X Cohen is an associate professor at the Radboud University Medical Center and the leader of the Synchronization in the Neural Systems research group. His research focuses on using state-of-the-art neuroscience methods to understand the mechanisms and implications of brain circuit dynamics and has been funded by government agencies in the US, Germany, Netherlands, and Europe, and by private institutions and medical centers.

Mike has been teaching time series analysis, applied mathematics, and scientific programming for almost 20 years. He has published several textbooks on these topics and teaches a variety of real-life and online courses.

Table of contents

  1. Chapter 1 : Introduction and Installations
    1. How to Get the Most Out of this Course!
    2. Using Python through Jupyter (Installing Anaconda)
    3. Using Python Online (No Installation)
    4. Create a Beautiful Harmonograph
    5. Getting Help in Python
  2. Chapter 2 : Arithmetic
    1. Addition, Subtraction, Multiplication, and Division
    2. Using Variables in Place of Numbers
    3. Printing Out Equations in Jupyter Notebook
    4. Writing Comments in Python
    5. Exponents (Powers)
    6. Using For-Loops to Compute Powers
    7. Order of Operations
    8. Testing Inequalities and Boolean Data Type
    9. Using If-Statements and Logical Operators
    10. Absolute Value
    11. Remainder After Division (Modulus)
    12. Create Interactive Math Functions, Part 1
    13. Create interactive math functions, Part 2
    14. Create interactive math functions, Part 3
    15. Arithmetic Bug Hunt!
  3. Chapter 3 : Introduction to SymPy and LaTeX
    1. Introduction to SymPy, Part 1
    2. Introduction to LaTeX
    3. Introduction to SymPy, Part 2
    4. Printing with F-Strings
    5. Example: Use SymPy to Understand the Law of Exponents
    6. SymPy/LaTeX Bug Hunt!
  4. Chapter 4 : Python Data Types
    1. Numbers and Strings
    2. Lists and NumPy Arrays
  5. Chapter 5 : Algebra 1
    1. Solving for X
    2. Solving for X: Exercises
    3. Expanding Terms
    4. Creating and Accessing Matrices with NumPy
    5. Exercise: Create a Multiplication Table
    6. Associative, Commutative, and Distributive Properties
    7. Creating and Working with Python Lists
    8. More on “Slicing” in Python
    9. Greatest Common Denominator
    10. Greatest Common Denominator: Exercises
    11. Introduction to Python Dictionaries
    12. Prime Factorization
    13. Solving Inequalities
    14. Adding Polynomials
    15. Multiplying Polynomials
    16. Dividing by Polynomials
    17. Factoring Polynomials
    18. Algebra 1 Bug Hunt!
  6. Chapter 6 : Graphing and Visualization
    1. Plotting Coordinates on a Plane
    2. Plotting Coordinates on a Plane: Exercise
    3. Graphing Lines - Part 1: Start/End Notation
    4. Graphing Lines - Part 2: Slope-Intercept Form
    5. Graphing Rational Functions
    6. Plotting with SymPy
    7. Plotting with SymPy: Exercises
    8. Course Tangent: Self-Accountability in Online Learning
    9. Making Images from Matrices
    10. Images from Matrices: Exercise
    11. Drawing Patches with Polygons
    12. Exporting Graphics as Pictures
    13. Graphing Bug Hunt!
  7. Chapter 7 : Algebra 2
    1. Summation and Products
    2. Differences (Discrete Derivative)
    3. Roots of Polynomials
    4. Roots of Polynomials: Exercise
    5. The Quadratic Equation
    6. Complex Numbers: Addition and Subtraction
    7. Complex Numbers: Conjugate and Multiplication
    8. Complex Numbers: Division
    9. Graphing Complex Numbers
    10. Revisiting the Quadratic Equation with Complex Numbers
    11. The Unit Circle
    12. Natural Exponent and Logarithm
    13. Find a Specific Point on a Gaussian
    14. Exercise: A Family of Gaussians
    15. Graphing the Complex Roots of Unity
    16. Log-Spaced and Linearly Spaced Numbers
    17. Logarithm Properties: Multiplication and Division
    18. Arithmetic and Geometric Sequences
    19. Orders of Magnitude and Scientific Notation
    20. Maxima and Minima of Functions
    21. Even and Odd Functions
    22. Algebra 2 Bug Hunt!
  8. Chapter 8 : Graphing Conic Sections
    1. Graphing Parabolas
    2. Creating Contours from Meshes in Python
    3. Graphing Circles
    4. Graphing Ellipses
    5. Graphing Hyperbolas
    6. Conic Bug Hunt!
  9. Chapter 9 : Trigonometry
    1. Introduction to Random Numbers
    2. Introduction to Random Numbers: Exercise
    3. Exercise: Plotting Random Phase Angles
    4. Converting between Radians and Degrees
    5. Converting Angles: Exercise
    6. The Pythagorean Theorem
    7. Graphing Resolution for Sine, Cosine, and Tangent
    8. Graphing and Resolution: Exercise
    9. Euler's Formula
    10. Euler's Formula: Exercise
    11. Exercise: Random Exploding Euler
    12. Exercise: Random Snakes with Cosine and Sine
    13. Trigonometry Bug Hunt!
  10. Chapter 10 : Art from Trigonometry
    1. Astroid Radial Curve
    2. Rose Curves
    3. Squircle
    4. Logarithmic Spiral
    5. Logistic Map
  11. Chapter 11 : Calculus
    1. Mathematical Proofs Versus Intuition with Examples
    2. Computing Limits of a Function
    3. Computing Limits: Exercise
    4. Piecewise Functions
    5. Derivatives of Polynomials
    6. Derivatives of Polynomials: Exercise
    7. Derivatives of Trig Functions
    8. Derivatives of Trig Functions: Exercise
    9. Graphing a Function Tangent Line
    10. Graphing Tangent Lines: Exercise
    11. Finding Critical Points
    12. Finding Critical Points: Exercise
    13. Partial Derivatives
    14. Indefinite and Definite Integrals
    15. Exercise: The Fundamental Theorem of Calculus
    16. Area between Two Curves
    17. Area between Two Curves: Exercise
    18. Calculus Bug Hunt!
  12. Chapter 12 : Linear Algebra
    1. Row and Column Vectors
    2. Adding and Scalar-Multiplying Vectors
    3. The Dot Product
    4. Dot Product Application: Correlation Coefficient
    5. The Outer Product
    6. Matrix Multiplication
    7. Transposing Vectors and Matrices
    8. Various Special Matrices
    9. Matrix Inverse
    10. Matrix Pseudoinverse: Exercise
    11. Solving a System of Equations
    12. Visualizing Matrix-Vector Multiplication
    13. Eigenvalues and Eigenvectors
    14. Eigendecomposition: Exercise
    15. Singular Value Decomposition
    16. SVD of Einstein: Exercise
    17. Linear Algebra Bug Hunt!
  13. Chapter 13 : Probabilities and Histograms
    1. Histograms and Probability Densities
    2. Probability Exercise: Math Functions
    3. Virtual Coin Tosses
    4. Exercise: Virtual Weighted Dice
    5. Building Distributions from Random Numbers
    6. Exercise: Normalize Any Distribution to Gaussian
    7. The Central Limit Theorem
    8. Exercise: The Central Limit Theorem
    9. Joint Probability Distributions
    10. Probability Bug Hunt!
  14. Chapter 14 : Number Theory
    1. Counting Perfect Numbers
    2. Euclid's Pythagorean Triplets
    3. Fermat's Theorem
    4. Plotting Number Sequences
    5. Exercise: Con/Divergent Sequences
    6. Heron's Method of Square Roots
    7. Exercise: Heron's Mosquito Spaceship #13
    8. Smooth Numbers
    9. Exercise: Smooth Numbers
    10. Number Theory Bug Hunt!

Product information

  • Title: Master Math by Coding in Python
  • Author(s): Codestars by Rob Percival, Mike X Cohen
  • Release date: August 2021
  • Publisher(s): Packt Publishing
  • ISBN: 9781801074537