Master Math by Coding in Python

BY
Udemy

Learn various mathematical concepts including algebra, calculus, graphing, trigonometry, and more using Python.

Mode

Online

Fees

₹ 3499

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study
Mode of Delivery Video and Text Based

Course overview

The Master Math by Coding in Python certification course was created by Codestars by Rob Percival in coordination with Mike X Cohen - Neuroscientist, Writer, and Professor and is available on Udemy for those interested in learning mathematics using the Python programming language. The Master Math by Coding in Python online course focuses on helping applicants gain expertise in python coding so that they may understand the principles of mathematics.

Master Math by Coding in Python online classes offers 37 hours of detailed learning lessons that are accompanied by 14 articles and 14 downloadable resources that cover all of the fundamental and advanced ways for applicants to study mathematics through python coding, Number theory, arithmetic, algebra, trigonometry, linear algebra, graphing, calculus, probability, and data visualization are among the topics covered in this course, which also discusses the functions of programs like LaTeX, Sympy, and Markdown.

The highlights

  • Certificate of completion
  • Self-paced course
  • 37 hours of pre-recorded video content
  • 1 articles
  • 1 downloadable resources

Program offerings

  • Online course
  • Learning resources. 30-day money-back guarantee
  • Unlimited access
  • Accessible on mobile devices and tv

Course and certificate fees

Fees information
₹ 3,499
certificate availability

Yes

certificate providing authority

Udemy

What you will learn

Mathematical skill Programming skills Knowledge of python

After completing the Master Math by Coding in Python online certification, applicants will be introduced to the functionality and methodologies associated with Python programming to learn mathematics and data visualization. Applicants will use Python to explore diverse mathematical procedures such as arithmetic, algebra, trigonometry, linear algebra, probability, Pythagorean triplets, Fermat's theorem, calculus, graphing, and histograms. Applicants will learn how to format equations in LaTeX and develop proficiency in combining Python, LaTeX, Sympy, and Markdown.

The syllabus

Introductions and installations

  • (Important) How to get the most out of this course!
  • Using Python through Jupyter (installing Anaconda)
  • Using Python online (no installation!)
  • Create a beautiful harmonograph!
  • Getting help in Python
  • (optional) Entering time-stamped notes in the Udemy video player

Arithmetic

  • Python code for this section
  • Addition, subtraction, multiplication, division
  • Using variables in place of numbers
  • Printing out equations in Jupyter notebook
  • Writing comments in Python
  • Exponents (powers)
  • Using for-loops to compute powers
  • Order of operations
  • Testing inequalities and Boolean data type
  • Using if-statements and logical operators
  • Absolute value
  • Remainder after division (modulus)
  • Create interactive math functions, part 1
  • Create interactive math functions, part 2
  • Create interactive math functions, part 3
  • Arithmetic bug hunt!

Introduction to Sympy and LaTeX

  • Python code for this section
  • Intro to Sympy, part 1
  • Intro to LaTeX
  • Intro to Sympy, part 2
  • Printing with f-strings
  • Example: Use Sympy to understand the law of exponents
  • Sympy/Latex bug hunt!

Python data types

  • Python codes for this section
  • Numbers and strings
  • Lists and numpy arrays

Algebra 1

  • Python code for this section
  • Solving for x
  • Solving for x: exercises
  • Expanding terms
  • Creating and accessing matrices with numpy
  • Exercise: Create a multiplication table
  • Associative, commutative, and distributive properties
  • Creating and working with Python lists
  • More on "slicing" in Python
  • Greatest common denominator
  • Greatest common denominator: exercises
  • Introduction to Python dictionaries
  • Prime factorization
  • Solving inequalities
  • Adding polynomials
  • Multiplying polynomials
  • Dividing by polynomials
  • Factoring polynomials
  • Algebra 1 bug hunt!

Graphing and visualization

  • Python code for this section
  • Plotting coordinates on a plane
  • Plotting coordinates on a plane: exercise
  • Graphing lines part 1: start/end notation
  • Graphing lines part 2: slope-intercept form
  • Graphing rational functions
  • Plotting with Sympy
  • Plotting with Sympy: exercises
  • Course tangent: self-accountability in online learning
  • Making images from matrices
  • Images from matrices: exercise
  • Drawing patches with polygons
  • Exporting graphics as pictures
  • Graphing bug hunt!

Algebra 2

  • Python code for this section
  • Summation and products
  • Differences (discrete derivative)
  • Roots of polynomials
  • Roots of polynomials: exercise
  • The quadratic equation
  • Complex numbers: addition and subtraction
  • Complex numbers: conjugate and multiplication
  • Complex numbers: division
  • Graphing complex numbers
  • Revisiting the quadratic equation with complex numbers
  • The unit circle
  • Natural exponent and logarithm
  • Find a specific point on a Gaussian
  • Exercise: A family of Gaussians
  • Graphing the complex roots of unity
  • Log-spaced and linearly spaced numbers
  • Logarithm properties: Multiplication and division
  • Arithmetic and geometric sequences
  • Orders of magnitude and scientific notation
  • Maxima and minima of functions
  • Even and odd functions
  • Algebra 2 bug hunt!

Graphing conic sections

  • Python code for this section
  • Graphing parabolas
  • Creating contours from meshes in Python
  • Graphing circles
  • Graphing ellipses
  • Graphing hyperbolas
  • Conic bug hunt!

Trigonometry

  • Python code for this section
  • Introduction to random numbers
  • Introduction to random numbers: exercise
  • Exercise: Plotting random phase angles
  • Converting between radians and degrees
  • Converting angles: exercise
  • The Pythagorean theorem
  • Graphing resolution for sine, cosine, and tangent
  • Graphing and resolution: Exercise
  • Euler's formula
  • Euler's formula: exercise
  • Exercise: random exploding Euler
  • Exercise: random snakes with cosine and sine
  • Trigonometry bug hunt!

Art from trigonometry

  • Python code for this section
  • Astroid radial curve
  • Rose curves
  • Squircle
  • Logarithmic spiral
  • Logistic map

Calculus

  • Python code for this section
  • Mathematical proofs vs. intuition with examples
  • Computing limits of a function
  • Computing limits: exercise
  • Piecewise functions
  • Derivatives of polynomials
  • Derivatives of polynomials: exercise
  • Derivatives of trig functions
  • Derivatives of trig functions: exercise
  • Graphing a function tangent line
  • Graphing tangent lines: exercise
  • Finding critical points
  • Finding critical points: exercise
  • Partial derivatives
  • Indefinite and definite integrals
  • Exercise: The fundamental theorem of calculus
  • Area between two curves
  • Area between two curves: exercise
  • Calculus bug hunt!

Linear algebra

  • Python code for this section
  • Row and column vectors
  • Adding and scalar-multiplying vectors
  • The dot product
  • Dot product application: Correlation coefficient
  • The outer product
  • Matrix multiplication
  • Transposing vectors and matrices
  • Various special matrices
  • Matrix inverse
  • Matrix pseudoinverse: exercise
  • Solving a system of equations
  • Visualizing matrix-vector multiplication
  • Eigenvalues and eigenvectors
  • Eigendecomposition: Exercise
  • Singular value decomposition
  • SVD of Einstein: exercise
  • Linear algebra BUG HUNT!

Probabilities and histograms

  • Python codes for this section
  • Histograms and probability densities
  • Probability exercise: math functions
  • Virtual coin tosses
  • Exercise: Virtual weighted dice
  • Building distributions from random numbers
  • Exercise: Normalize any distribution to Gaussian
  • The central limit theorem
  • Exercise: the central limit theorem
  • Joint probability distributions
  • Probability bug hunt!

Number theory

  • Python codes for this section
  • Counting perfect numbers
  • Euclid's Pythagorean triplets
  • Fermat's theorem
  • Plotting number sequences
  • Exercise: con/divergent sequences
  • Heron's method of square roots
  • Exercise: Heron's mosquito spaceship #13
  • Smooth numbers
  • Exercise: Smooth numbers
  • Number theory bug hunt!

Bonus section

  • Bonus lecture

Instructors

Mr Mike X Cohen

Mr Mike X Cohen
Associate Professor
Freelancer

Articles

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