Doing Math with Python

Doing Math with Python, available at $44.99, has an average rating of 4.25, with 80 lectures, based on 6 reviews, and has 2112 subscribers.

You will learn about Using Python, be able to explore high school level mathematical topics Learn how to programming data with graphs using Python Learn how to describing data with statistics Grasp Algebra and Symbolic Math with SymPy in Python Learn how to play with sets and probablility Learn hwo to drawing geometric shaps and fractals Using Python to solve certain calculus problems This course is ideal for individuals who are Anyone who are planning to learn programming or Anyone who want to learn programming to solve problems with computers or Anyone have interests on combining mathematics with Python language or Anyone what to get deeper practical experience on Python It is particularly useful for Anyone who are planning to learn programming or Anyone who want to learn programming to solve problems with computers or Anyone have interests on combining mathematics with Python language or Anyone what to get deeper practical experience on Python.

Enroll now: Doing Math with Python

Summary

Title: Doing Math with Python

Price: $44.99

Average Rating: 4.25

Number of Lectures: 80

Number of Published Lectures: 80

Number of Curriculum Items: 80

Number of Published Curriculum Objects: 80

Original Price: CA$99.99

Quality Status: approved

Status: Live

What You Will Learn

Using Python, be able to explore high school level mathematical topics

Learn how to programming data with graphs using Python

Learn how to describing data with statistics

Grasp Algebra and Symbolic Math with SymPy in Python

Learn how to play with sets and probablility

Learn hwo to drawing geometric shaps and fractals

Using Python to solve certain calculus problems

Who Should Attend

Anyone who are planning to learn programming

Anyone who want to learn programming to solve problems with computers

Anyone have interests on combining mathematics with Python language

Anyone what to get deeper practical experience on Python

Target Audiences

Anyone who are planning to learn programming

Anyone who want to learn programming to solve problems with computers

Anyone have interests on combining mathematics with Python language

Anyone what to get deeper practical experience on Python

With this course, we’ll go through the nice book “Doing Math with Python” (authored by Amit Saha) in full detail, demo to you every touched mathematical topics, like

manipulating units of measurement;

examining projectile motion;

calculating mean, median, and mode;

determining linear correlation;

solving algebraic equations;

describing the motion of a simple pendulum;

simulating dice games;

creating geometric shapes;

and finding the limits, derivatives, and integrals of functions.

After the course, you’ll be able write programes to take numbers and formulas as input, do the tedious calculations needed, and then spit out the solution or draw a graph.

You’ll have chances to follow several programming challenges, you’ll find those programs are powerful calculators for solving math problems. You’ll also find the solutions to equations, calculate the correlation between sets of data, and determine the maximum value of a function, among other tasks. You’ll also take some practice to simulate real-life events, such as projectile motions, a coin toss, or a die roll.

As mentioned by the book author, I do hope “you’ll find that this new context for ‘doing math’ makes learning both programming and math more exciting, fun, and rewarding.”

So, what you’re still waitomg fpr? Let’s start now and good luck!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Opening and Introduction

Chapter 2: Chapter 1: Working with Numbers

Lecture 1: 01-01 Basic Mathematical Operations

Lecture 2: 01-02 Labels: Attaching Names to Numbers, 01-03 Differnt Kind s of Numbers

Lecture 3: 01-04 Getting User Input

Lecture 4: 01-05 Writing Programs that Do the Math (Part 1)

Lecture 5: 01-05 Writing Programs that Do the Math (Part 2) – Multiplication Table

Lecture 6: 01-05 Writing Programs that Do the Math (Part 3) – Measurement Unit Converter

Lecture 7: 01-05 Writing Programs that Do the Math (Part 4) – One Math Calculator

Lecture 8: Challenges #1: Even-Odd Vending Machine

Lecture 9: Challenges #2: Enhanced Multiplication Table Generator

Lecture 10: Challenges #3: Enhanced Unit Converter

Lecture 11: Challenges #4: Fraction Calculator

Lecture 12: Challenges #5: Give Exit Power to the User

Chapter 3: Chapter 2: Visualizing Data with Graphs

Lecture 1: 02-01 Understanding the Cartesian Coordinate Plane

Lecture 2: 02-02 Working with Lists and Tuples

Lecture 3: 02-03 Creating Graphs with Matplotlib (& pylab)

Lecture 4: 02-04 Plotting with Formulas (Part 1) – Newtons Las of Universal Gravitation

Lecture 5: 02-04 Plotting with Formulas (Part 2) – Projectile Motion

Lecture 6: 02-05 Programming Challenges #1: Vary Temperature in a Day

Lecture 7: 02-05 Programming Challenges #2: Visualize Quadratic Function

Lecture 8: 02-05 Programming Challenges #3: Enhanced Projectile Trajectory Comaprison Prog.

Lecture 9: 02-05 Programming Challenges #4: Visualizing Your Expenses

Lecture 10: 02-05 Programming Challenges #5: Relationship between Fib. Seq. & Golden Ratio

Chapter 4: Chapter 3: Describing Data with Statistics

Lecture 1: 03-01 Find the Mean

Lecture 2: 03-02 Find the Median

Lecture 3: 03-03 Finding the Mode and Creating a Frequency Table

Lecture 4: 03-04 Measuring the Dispersion

Lecture 5: 03-05 Calculate the Correlation (Part 1)

Lecture 6: 03-05 Calculate the Correlation (Part 2)

Lecture 7: 03-06 Scatter Plots

Lecture 8: 03-07 Reading Data from Files (Part 1): Text File

Lecture 9: 03-07 Reading Data from Files (Part 2): CSV File

Lecture 10: 03-08 Programming Challenges #1: Better Correlation Coefficient-Finding Program

Lecture 11: 03-08 Programming Challenges #2: Statistics Calculator

Lecture 12: 03-08 Programming Challenges #3: Experiment with Other CSV Data

Lecture 13: 03-08 Programming Challenges #4: Finding the Percentile (1)

Lecture 14: 03-08 Programming Challenges #4: Finding the Percentile (2)

Lecture 15: 03-08 Programming Challenges #5: Generate a Grouped Frequency Table

Chapter 5: Chapter 4: Algebra and Symbolic Math with Sympy

Lecture 1: 04-00 Installing and Configuring SymPy

Lecture 2: 04-01 Defining Symbols and Symbolic Operations

Lecture 3: 04-02 Working with Expressions

Lecture 4: 04-03 Solving Equations

Lecture 5: 04-04 Plotting Using SymPy

Lecture 6: 04-05 Programming Challenges #1: Factor Finder

Lecture 7: 04-05 Programming Challenges #2: Graphical Equation Solver

Lecture 8: 04-05 Programming Challenges #3: Summing a Series

Lecture 9: 04-05 Programming Challenges #4: Solving Single-Variable Inequalities

Chapter 6: Chapter 5: Playing with Sets and Probability

Lecture 1: 05-01 What is a Set? (1) – Concepts, Set Construction

Lecture 2: 05-01 What is a Set? (2) – Sets Relationships

Lecture 3: 05-01 What is a Set? (3) – Set Operations

Lecture 4: 05-02 Probability (0) Concept (1) Or (2) And

Lecture 5: 05-02 Probability (3) Generating Random Numbers

Lecture 6: 05-02 Probability (4) Non-Uniform Random Numbers

Lecture 7: 05-03 Programming Challenges #1: Using Venn Diagrams to Visual Relation of Sets

Lecture 8: 05-03 Programming Challenges #2: Law of Large Numbers

Lecture 9: 05-03 Programming Challenges #3: How Many Tosses Before You Run Out of Memory?

Lecture 10: 05-03 Programming Challenges #4: Shuffling a Deck of Cards

Lecture 11: 05-03 Programming Challenges #5: Estimating the Area of a Circle

Chapter 7: Chapter 6: Drawing Geometric Shapes and Fractals

Lecture 1: 06-01 Drawing Geometrics Shapes with Matplotlibs Patches #1: Drawing a Circle

Lecture 2: 06-01 Drawing Geometrics Shapes with Matplotlibs Patches #2 Create Animate Fig.

Lecture 3: 06-01 Drawing Geometrics Shapes with Matplotlibs Patches #3 Anim. Proj. Trajec.

Lecture 4: 06-02 Drawing Fractals #1: Transformations of Points in a Plane

Lecture 5: 06-02 Drawing Fractals #2 Drawing the Barnsley Fern

Lecture 6: 06-03 Programming Challenges #1 Packing Circles into a Square

Lecture 7: 06-03 Programming Challenges #2 Draw Sierpinski Triangle

Lecture 8: 06-03 Programming Challenges #3 Explore Henons Function

Lecture 9: 06-03 Programming Challenges #4 Drawing Mandelbrot Set (part 1 & 2)

Lecture 10: 06-03 Programming Challenges #4 Drawing Mandelbrot Set (Part 3)

Chapter 8: Chapter 7: Solving Claculus Problems

Lecture 1: 07-01 What is a Function

Lecture 2: 07-02 Assumption in SymPy, 07-03 Finding the Limit of Functions

Lecture 3: 07-04 Finding the Derivative of Functions

Lecture 4: 07-05 Higher-Order Derivatives and Finding the Maxima and Minima

Lecture 5: 07-06 Finding the Global Maximum using Gradient Ascent #0 and #1

Lecture 6: 07-06 Finding the Global Maximum using Gradient Ascent #2 and #3

Lecture 7: 07-07 Finding the Integrals of Functions, 07-08 Probability Density Functions

Lecture 8: 07-09 Programming Challenges #1: Verify the Continuity of a Function at a Point

Lecture 9: 07-09 Programming Challenges #2: Implement the Gradient Descent

Lecture 10: 07-09 Programming Challenges #3: Area Between Two Curves

Lecture 11: 07-09 Programming Challenges #4: Finding the Length of a Curve

Chapter 9: Summary

Lecture 1: Summary and Closing

Instructors

Xiaoqi Zhao
Enterrpise Architect and Modeling Practitioner

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5 stars: 2 votes

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