Master College Algebra with this Free Python-Powered Course
In today‘s data-driven world, strong math skills are more valuable than ever, especially for those pursuing careers in computer science, software engineering, data analysis, and artificial intelligence. College Algebra, in particular, is a fundamental course that lays the groundwork for success in these lucrative and in-demand fields.
According to the U.S. Bureau of Labor Statistics, employment in computer and information technology occupations is projected to grow 13% from 2020 to 2030, adding about 667,600 new jobs. This growth is faster than the average for all occupations, and the median annual wage for these roles is $91,250, more than double the median for all occupations.1
However, many students struggle with algebra, finding it abstract and disconnected from their interests. That‘s where this free College Algebra course comes in – it teaches algebra through the lens of Python programming, making the math concrete, interactive, and relevant to real-world problems.
Course Overview
| Feature | This Course | Typical Online Course |
|---|---|---|
| Delivery Format | Videos & interactive coding | Videos or text only |
| Content Coverage | Full college semester | Varies widely |
| Python Programming | Integrated throughout | Not included |
| Instructor Credentials | PhD in Math & CS, 20+ years experience | Often less experienced or credentialed |
| Problem-Solving Focus | Strong emphasis | Varies |
| Interactivity | High, with coding exercises | Low to moderate |
| Real-World Applications | Demonstrated with Python examples | Often lacking |
| Price | Free | $50 to $500+ |
This 15-week course, instructed by Dr. James Maxwell (PhD in Mathematics and Computer Science), covers all the key topics of a typical college algebra curriculum, including:
- Fundamental operations and properties
- Solving linear and quadratic equations
- Graphing functions
- Working with polynomials, rational expressions, and radicals
- Exponential and logarithmic functions
- Sequences and series
- Introduction to counting and probability
What sets this course apart is that each concept is not only thoroughly explained from a mathematical perspective, but also implemented in Python code. This dual approach deepens understanding and showcases the practical power of algebra.
Through video lessons and hands-on coding in Google Colab notebooks, students build their own library of Python functions for tasks like evaluating expressions, solving equations, graphing functions, and more. This unique integration of math and programming offers several key benefits:
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Improved problem-solving skills: Coding requires breaking down problems into step-by-step solutions, a skill that transfers to math and other domains.
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Enhanced logical thinking: Programming promotes rigorous, systematic reasoning – a cornerstone of mathematical thinking.
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Practical applications: Students see how algebra is used in real-world coding contexts, making the math more concrete and relevant.
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Marketable skills: Familiarity with Python, a leading language for data science and machine learning, boosts career prospects in tech.
Dr. Maxwell draws on his extensive experience as a researcher, educator, and software engineer to craft engaging lessons that resonate with students. He has taught math and computer science at both the undergraduate and graduate level, and has developed numerous popular coding courses and tutorials.
Addressing Common Struggles
Many students find algebra challenging due to its abstractness and perceived disconnect from their interests and goals. This course tackles these issues head-on by:
- Grounding concepts in concrete coding examples
- Emphasizing practical applications and problem-solving
- Providing ample opportunities for hands-on practice
- Building coding projects that leverage algebra skills
- Fostering a supportive community of learners and instructors
The course also includes supplemental resources and mini-lessons to target common pain points, such as:
- Refreshers on pre-algebra fundamentals like order of operations and properties of real numbers
- Tutorials on effectively using Python libraries for algebra and data visualization, such as SymPy and Matplotlib
- Tips for breaking down word problems and translating them into algebraic expressions
- Walkthroughs of example problems with step-by-step explanations
- Strategies for checking work and debugging errors in both math and code
By anticipating and addressing these challenges, the course sets students up for success and helps them build confidence in their abilities.
A Week-by-Week Breakdown
To give you a clearer picture of the learning journey, here‘s a closer look at what each week of the course covers:
Week 1: Algebra Essentials
- Real number system properties
- Order of operations
- Simplifying expressions
- Translating words into algebraic expressions
- Basic Python syntax and operations
Week 2: Linear Equations
- Solving one-step, two-step, and multi-step equations
- Solving equations with variables on both sides
- Identifying equations vs. expressions vs. functions
- Implementing equation solvers in Python
Week 3: Graphing Linear Equations
- Slope and y-intercept
- Graphing lines using slope and y-intercept
- Horizontal and vertical lines
- Graphing lines with Python‘s Matplotlib library
Week 4: Systems of Linear Equations
- Solving systems by graphing, substitution, and elimination
- Identifying consistent, inconsistent, and dependent systems
- Applications of systems (cost, mixture, distance/rate/time problems)
- Solving and graphing systems with Python
Week 5: Polynomials
- Classifying and naming polynomials
- Adding, subtracting, and multiplying polynomials
- Special products (binomial squares, difference of squares, sum/difference of cubes)
- Implementing polynomial operations in Python
Week 6: Factoring
- Greatest common factor and factor by grouping
- Factoring trinomials
- Solving quadratic equations by factoring
- Coding factoring techniques in Python
Week 7: Quadratic Functions
- Quadratic function graphs
- Vertex form and transformations
- Quadratic formula and discriminant
- Graphing quadratics and finding roots in Python
Week 8: Exponential and Logarithmic Functions
- Evaluating and graphing exponential functions
- Solving exponential equations with logarithms
- Change of base formula
- Implementing exponential and log functions in Python
Week 9: Rational Expressions and Functions
- Simplifying and operating with rational expressions
- Solving rational equations
- Graphing rational functions
- Horizontal and vertical asymptotes
- Coding rational expression operations and graphing
Week 10: Radical Expressions and Functions
- Simplifying radicals
- Solving radical equations
- Graphing square root and cube root functions
- Coding radical simplification and graphing
Week 11: Sequences and Series
- Arithmetic and geometric sequences
- Recursive and explicit formulas
- Summation notation and partial sums
- Infinite geometric series
- Generating sequences and series with Python
Week 12: Counting and Probability Basics
- Fundamental counting principle
- Permutations and combinations
- Basic probability rules
- Probability distributions (binomial, Poisson, normal)
- Simulating probability experiments in Python
Weeks 13-14: Applications and Final Project
- Algebra in business, economics, physics, and computer science
- Solving complex real-world problems
- Building a substantial coding project showcasing course skills
Week 15: Wrap-up and Next Steps
- Course review and reflection
- Connecting algebra to future math and CS courses
- Resources for continuing to learn and practice
- Strategies for applying skills in academic and professional contexts
Throughout the course, students also complete auto-graded quizzes to reinforce their understanding and get immediate feedback. They can discuss questions and insights with classmates and instructors in the course forums, and access additional resources to dive deeper into topics of interest.
A Powerful Toolkit for Algebra and Beyond
In addition to mastering fundamental algebra concepts, students come away from this course with an impressive toolkit of Python skills for doing math, including:
- Representing mathematical objects like numbers, expressions, and equations in Python code
- Using Python libraries like SymPy for symbolic math and Matplotlib for data visualization
- Writing custom functions to automate algebraic computations and generalizing problem-solving steps
- Applying programming concepts like variables, functions, loops, and conditionals to enhance mathematical thinking
- Analyzing real-world datasets using algebra and Python to uncover insights and patterns
These skills are highly transferable to further studies in math, science, and computing, as well as to research and industry work. Students are equipped to use their newfound coding abilities to tackle more advanced math courses, analyze data for projects or businesses, build interactive math tools and simulations, and more.
Getting Started
Ready to begin your algebra adventure? Dive into the course videos and coding notebooks at the course YouTube playlist. Take the course at your own pace, engaging with the quizzes and exercises to build your skills. Join the discussion forums to ask questions, share insights, and connect with your fellow learners and instructors.
As you journey through the course, remember that math is not about memorizing formulas, but about creatively solving problems. Embrace challenges, learn from mistakes, and celebrate your progress. With dedication and practice, you‘ll be amazed at how much you can achieve.
By the end of this course, you‘ll have a rock-solid foundation in algebra and a powerful set of Python tools to apply your skills in the real world. Whether your goal is to ace your math classes, pursue a career in tech, or simply expand your intellectual horizons, this course will help you get there.
So what are you waiting for? Start your algebra journey today and unlock a world of mathematical possibilities!
1 U.S. Bureau of Labor Statistics. (2021, September 8). Computer and Information Technology Occupations. https://www.bls.gov/ooh/computer-and-information-technology/home.htm