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
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manipulating units of measurement;
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examining projectile motion;
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calculating mean, median, and mode;
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determining linear correlation;
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solving algebraic equations;
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describing the motion of a simple pendulum;
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simulating dice games;
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creating geometric shapes;
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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 Matplotlib's Patches #1: Drawing a Circle
Lecture 2: 06-01 Drawing Geometrics Shapes with Matplotlib's Patches #2 Create Animate Fig.
Lecture 3: 06-01 Drawing Geometrics Shapes with Matplotlib's 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 Henon's 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
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Xiaoqi Zhao
Enterrpise Architect and Modeling Practitioner
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- 4 stars: 2 votes
- 5 stars: 2 votes
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