The Language of Mathematics — and the Gateway to Every STEM Field
About This Class
Algebra I is where mathematics becomes a genuine language. We use symbols and equations to model real situations, predict outcomes, and solve problems that have no obvious arithmetic path. This course covers functions, linear and quadratic relationships, systems of equations, and data analysis.
These aren't abstract concepts invented by mathematicians for other mathematicians. They're the tools economists use to model markets, scientists use to describe natural phenomena, and engineers use to design the systems that run the world. When a social media algorithm decides what you see next, that's algebra. When a business decides where to open a new location, that's a system of inequalities.
We'll use graphing calculators, Desmos, and real-world data throughout the year. The goal is fluency — being able to read, write, and speak algebra with confidence.
Function notation, domain and range, multiple representations
Slope-intercept form, point-slope, graphing, systems, applications
Substitution, elimination, graphing, and real-world problem solving
Operations with polynomials, factoring, and special products
Standard form, vertex form, factoring, quadratic formula, applications
Math in the Real World
The algorithms that decide what you see on Instagram, TikTok, and YouTube are built on functions and linear modeling — core Algebra I concepts. Every "For You" page is generated by hundreds of equations running simultaneously.
Profit and loss analysis, break-even calculations, and pricing strategy all rely on linear equations and systems. A business owner deciding when a new product will become profitable is solving a system of equations — often without realizing it.
Trajectory, projectile motion, and gravitational pull are all modeled with quadratic functions. Engineers at NASA use these same equations to calculate rocket paths. Game developers use them to make objects bounce and fall realistically.
Data scientists use linear regression — lines of best fit — to find patterns in massive datasets and make predictions. The foundation? Slope, y-intercept, and understanding what a linear function means. It scales to millions of data points.
Lesson Plans
Click any highlighted date to jump to that lesson. Lesson plan PDFs will be linked here as they are posted — check back regularly throughout the semester.
Highlighted dates have lesson plans attached. Use the arrows to browse past or future months.