English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 29 Hours | 7.88 GB
Use Python to learn algebra, calculus, graphing, trigonometry and more math topics!
You can learn a lot of math with a bit of coding!
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.
This course is a perfect supplement to your school/university math course, or for your post-school return to mathematics.
Let me guess what you are thinking:
“But I don’t know Python!” That’s okay! This course is aimed at complete beginners; I 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.
“But I’m not good at math!” You will be amazed at how much better you can learn math by 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.
What do you get in this course?
Over 28 hours of instruction that includes Python coding, visualization, loops, variables, and functions.
LOTS of practical exercises! Each video has at least one hands-on coding/math exercise (and you’ll get to watch me solve those exercises). And each section ends with “bug hunts” where you get to find and fix my math-coding errors!
That warm, fuzzy feeling of confidence that you can combine the skills from this course to improve your understanding of mathematics.
A big-picture overview of beginner and advanced mathematics, from solving for “x” to computing integrals to finding eigenvalues. If you are only just beginning your adventures in maths, then this course will show you what you have to look forward to!
This course is right for you if you are:
In middle/high school, university, or are returning to math as an independent learner.
A data professional who wants to brush up on math and Python skills.
A complete beginner to Python.
Already proficient with math “in theory” and want to learn how to translate math formulas and concepts into computer code.
Bored and looking for a fun intellectual challenge.
All the code that appears in the videos is also included for download. You can code along as you watch the videos, or download the code and use it directly.
This course covers the following topics:
Introduction to Sympy
- Introduction to LaTeX (to print beautiful equations!)
- Algebra 1
- Algebra 2
- Graphing conic sections
- Linear algebra
- …and more!
What you’ll learn
- Most important: Confidence in learning math!
- Algebra (1, 2)
- Linear algebra
- Python programming
- Formatting beautiful equations in LaTeX
- Data visualization
- Integrating Python, Markdown, and LaTeX
Introductions and installations
1 (Important) How to get the most out of this course!
2 Using Python through Jupyter (installing Anaconda)
3 Using Python online (no installation!)
4 Getting help in Python
5 Python code for this section
6 Using if-statements and logical operators
7 Absolute value
8 Remainder after division (modulus)
9 Create interactive math functions, part 1
10 Create interactive math functions, part 2
11 Create interactive math functions, part 3
12 Arithmetic bug hunt!
13 Addition, subtraction, multiplication, division
14 Using variables in place of numbers
15 Printing out equations in Jupyter notebook
16 Writing comments in Python
17 Exponents (powers)
18 Using for-loops to compute powers
19 Order of operations
20 Testing inequalities and Boolean data type
Introduction to Sympy and LaTeX
21 Python code for this section
22 Intro to Sympy, part 1
23 Intro to LaTeX
24 Intro to Sympy, part 2
25 Example Use Sympy to understand the law of exponents
26 SympyLatex bug hunt!
27 Python code for this section
28 Greatest common denominator
29 Greatest common denominator exercises
30 Introduction to Python dictionaries
31 Prime factorization
32 Solving inequalities
33 Adding polynomials
34 Multiplying polynomials
35 Dividing by polynomials
36 Factoring polynomials
37 Algebra 1 bug hunt!
38 Solving for x
39 Solving for x exercises
40 Expanding terms
41 Creating and accessing matrices with numpy
42 Exercise Create a multiplication table
43 Associative, commutative, and distributive properties
44 Creating and working with Python lists
45 More on slicing in Python
Graphing and visualization
46 Python code for this section
47 Images from matrices exercise
48 Drawing patches with polygons
49 Exporting graphics as pictures
50 Graphing bug hunt!
51 Plotting coordinates on a plane
52 Plotting coordinates on a plane exercise
53 Graphing lines part 1 startend notation
54 Graphing lines part 2 slope-intercept form
55 Graphing rational functions
56 Plotting with Sympy
57 Plotting with Sympy exercises
58 Making images from matrices
59 Python code for this section
60 Graphing complex numbers
61 Revisiting the quadratic equation with complex numbers
62 The unit circle
63 Natural exponent and logarithm
64 Graphing the complex roots of unity
65 Log-spaced and linearly spaced numbers
66 Arithmetic and geometric sequences
67 Orders of magnitude and scientific notation
68 Maxima and minima of functions
69 Even and odd functions
70 Summation and products
71 Algebra 2 bug hunt!
72 Differences (discrete derivative)
73 Roots of polynomials
74 Roots of polynomials exercise
75 The quadratic equation
76 Complex numbers addition and subtraction
77 Complex numbers conjugate and multiplication
78 Complex numbers division
Graphing conic sections
79 Python code for this section
80 Graphing parabolas
81 Creating contours from meshes in Python
82 Graphing circles
83 Graphing ellipses
84 Graphing hyperbolas
85 Conic bug hunt!
86 Python code for this section
87 Euler’s formula
88 Euler’s formula exercise
89 Exercise random exploding Euler
90 Exercise random snakes with cosine and sine
91 Trigonometry bug hunt!
92 Introduction to random numbers
93 Introduction to random numbers exercise
94 Exercise Plotting random phase angles
95 Converting between radians and degrees
96 Converting angles exercise
97 The Pythagorean theorem
98 Graphing resolution for sine, cosine, and tangent
99 Graphing and resolution Exercise
100 Python code for this section
101 Graphing a function tangent line
102 Graphing tangent lines exercise
103 Finding critical points
104 Finding critical points exercise
105 Partial derivatives
106 Indefinite and definite integrals
107 Exercise The fundamental theorem of calculus
108 Area between two curves
109 Area between two curves exercise
110 Calculus bug hunt!
111 Mathematical proofs vs. intuition with examples
112 Computing limits of a function
113 Computing limits exercise
114 Piecewise functions
115 Derivatives of polynomials
116 Derivatives of polynomials exercise
117 Derivatives of trig functions
118 Derivatives of trig functions exercise
119 Python code for this section
120 Matrix inverse
121 Matrix pseudoinverse exercise
122 Solving a system of equations
123 Visualizing matrix-vector multiplication
124 Eigenvalues and eigenvectors
125 Eigendecomposition Exercise
126 Singular value decomposition
127 SVD of Einstein exercise
128 Linear algebra BUG HUNT!
129 Row and column vectors
130 Adding and scalar-multiplying vectors
131 The dot product
132 Dot product application Correlation coefficient
133 The outer product
134 Matrix multiplication
135 Transposing vectors and matrices
136 Various special matrices
137 Related courses