Algebra and Differential Calculus for Data Science (Coursera)

Algebra and Differential Calculus for Data Science (Coursera)

Are you interested in Data Science but lack the math background for it? Has math always been a tough subject that you tend to avoid? This course will teach you the most fundamental Calculus concepts that you will need for a career in Data Science without a ton of unnecessary proofs and techniques that you may never use.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

Consider this an expressway to Data Science with approachable methods and friendly concepts that will guide you to truly understanding the most important ideas in Differential Calculus. We will review some algebra basics, talk about what a derivative is, compute some simple derivatives and apply the basics of derivatives to graphing and maximizing functions.
This course is designed to prepare learners to successfully complete Statistical Modeling for Data Science Application, which is part of CU Boulder's Master of Science in Data Science (MS-DS) program.

What You Will Learn

  • Practice working with logarithm properties and how logarithm functions behave graphically.
  • Identify the difference between a continuous and non-continuous function.
  • Solidify an understanding of what a derivative is calculating.
  • Understand how to use derivatives to create graphs of functions.

Syllabus

WEEK 1
Functions and Algebra Review
Review of algebra concepts including functions and logarithms

WEEK 2
Induction Proofs, Limits and Continuity
Simple induction proofs and limits at infinity for functions

WEEK 3
Definition of a Derivative
What is a derivative? Calculate simple derivatives from the definition of a derivative.

WEEK 4
Product and Chain Rule
Use the product and chain rules to calculate the derivatives of more complicated functions.

WEEK 5
Using Derivatives to Graph Functions
Use where derivatives are positive and negative to help graph a function.

WEEK 6
Finding Maximums and Minimums
Use derivatives to find the maximum and minimum values of functions.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Calculus: Single Variable Part 2 - Differentiation (Coursera) Coursera
University of Pennsylvania

Calculus: Single Variable Part 2 - Differentiation (Coursera)

Calculus is one of the grandest achievements of human thought, explaining everything from planetary orbits to the optimal size of a city to the periodicity of a heartbeat. This brisk course covers the core ideas of single-variable Calculus with emphases on conceptual understanding and applications. The course is ideal for students beginning in the engineering, physical, and social sciences.

Jun 8th 2026
3 Weeks
Calculus: Single Variable Part 3 - Integration (Coursera) Coursera
University of Pennsylvania

Calculus: Single Variable Part 3 - Integration (Coursera)

Calculus is one of the grandest achievements of human thought, explaining everything from planetary orbits to the optimal size of a city to the periodicity of a heartbeat. This brisk course covers the core ideas of single-variable Calculus with emphases on conceptual understanding and applications. The course is ideal for students beginning in the engineering, physical, and social sciences.

Jun 8th 2026
4 Weeks
TSI Math Prep MOOC (Coursera) Coursera
University of North Texas

TSI Math Prep MOOC (Coursera)

The purpose of this course is to review and practice key concepts in preparation for the math portion of the Texas Success Initiative Assessment 2.0 (TSI2). The TSI2 is series of placement tests for learners enrolling in public universities in Texas. This MOOC will cover the four main categories of the Mathematics portion: Quantitative Reasoning, Algebraic Reasoning, Geometric & Spatial Reasoning, and Probabilistic & Statistical Reasoning.

Jun 8th 2026
4 Weeks
Matrix Algebra for Engineers (Coursera) Coursera
The Hong Kong University of Science and Technology - HKUST

Matrix Algebra for Engineers (Coursera)

This course is all about matrices, and concisely covers the linear algebra that an engineer should know. The mathematics in this course is presented at the level of an advanced high school student, but typically students should take this course after completing a university-level single variable calculus course. There are no derivatives or integrals in this course, but students are expected to have attained a sufficient level of mathematical maturity. Nevertheless, anyone who wants to learn the basics of matrix algebra is welcome to join.

Jun 8th 2026
4 Weeks
Linear Regression and Modeling (Coursera) Coursera
Duke University

Linear Regression and Modeling (Coursera)

This course introduces simple and multiple linear regression models. These models allow you to assess the relationship between variables in a data set and a continuous response variable. Is there a relationship between the physical attractiveness of a professor and their student evaluation scores? Can we predict the test score for a child based on certain characteristics of his or her mother? In this course, you will learn the fundamental theory behind linear regression and, through data examples, learn to fit, examine, and utilize regression models to examine relationships between multiple variables, using the free statistical software R and RStudio.

Jun 8th 2026
4 Weeks
Algebra: Elementary to Advanced - Functions & Applications (Coursera) Coursera
Johns Hopkins University

Algebra: Elementary to Advanced - Functions & Applications (Coursera)

After completing this course, students will learn how to successfully apply functions to model different data and real world occurrences. This course reviews the concept of a function and then provide multiple examples of common and uncommon types of functions used in a variety of disciplines. Formulas, domains, ranges, graphs, intercepts, and fundamental behavior are all analyzed using both algebraic and analytic techniques. From this core set of functions, new functions are created by arithmetic operations and function composition.

Jun 8th 2026
3 Weeks
Differential Equations for Engineers (Coursera) Coursera
The Hong Kong University of Science and Technology - HKUST

Differential Equations for Engineers (Coursera)

This course is about differential equations and covers material that all engineers should know. Both basic theory and applications are taught. In the first five weeks we will learn about ordinary differential equations, and in the final week, partial differential equations. The course is composed of 56 short lecture videos, with a few simple problems to solve following each lecture. And after each substantial topic, there is a short practice quiz. Solutions to the problems and practice quizzes can be found in instructor-provided lecture notes. There are a total of six weeks in the course, and at the end of each week there is an assessed quiz.

Jun 8th 2026
5-12 Weeks
Advanced Linear Models for Data Science 2: Statistical Linear Models (Coursera) Coursera
Johns Hopkins University

Advanced Linear Models for Data Science 2: Statistical Linear Models (Coursera)

Welcome to the Advanced Linear Models for Data Science Class 2: Statistical Linear Models. This class is an introduction to least squares from a linear algebraic and mathematical perspective. Before beginning the class make sure that you have the following: a basic understanding of linear algebra and multivariate calculus; a basic understanding of statistics and regression models; at least a little familiarity with proof based mathematics; basic knowledge of the R programming language.

Jun 8th 2026
4 Weeks
Calculus through Data & Modelling: Vector Calculus (Coursera) Coursera
Johns Hopkins University

Calculus through Data & Modelling: Vector Calculus (Coursera)

This course continues your study of calculus by focusing on the applications of integration to vector valued functions, or vector fields. These are functions that assign vectors to points in space, allowing us to develop advanced theories to then apply to real-world problems. We define line integrals, which can be used to fund the work done by a vector field. We culminate this course with Green's Theorem, which describes the relationship between certain kinds of line integrals on closed paths and double integrals.

Jun 8th 2026
3 Weeks