Data Science Math Skills
Master essential math for data science: Set theory, real numbers, functions, calculus basics, and probability theory for aspiring data scientists.
Course Cost
₹ 2,699
Beginner
Skill Level
12 Hours
Self-paced lessons
This comprehensive course introduces the fundamental math skills required for data science. Designed for learners with basic math knowledge, it covers essential topics like set theory, real number properties, interval notation, algebra with inequalities, Cartesian plane graphing, functions, derivatives, exponents, logarithms, and probability theory including Bayes' theorem. The course aims to build a strong foundation in mathematical concepts and notation used in data science, preparing learners for more advanced material. With a focus on clear explanations and practical applications, it's an ideal starting point for those looking to enter the field of data science or strengthen their mathematical background.
What you'll learn
Master set theory concepts including Venn diagrams and their applications
Understand real number properties, interval notation, and algebra with inequalities
Learn to use summation and Sigma notation for statistical calculations
Graph and describe functions on the Cartesian plane, including slope and distance formulas
Grasp basic calculus concepts like instantaneous rate of change and tangent lines
Explore exponents, logarithms, and the natural log function
Develop a strong foundation in probability theory, including Bayes' theorem
Skills you'll gain
This course includes:
5 Hours PreRecorded video
14 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.





There are 4 modules in this course
This course provides a comprehensive introduction to the essential mathematical skills needed for data science. It covers fundamental topics such as set theory, properties of real numbers, interval notation, algebra with inequalities, graphing on the Cartesian plane, functions and their inverses, basic calculus concepts like derivatives, exponents and logarithms, and probability theory including Bayes' theorem. The course is designed to build a strong foundation in mathematical concepts and notation used in data science, preparing learners for more advanced material. With a focus on clear explanations and practical applications, it's an ideal starting point for those looking to enter the field of data science or strengthen their mathematical background.
Building Blocks for Problem Solving
Module 1 · 3 Hours to complete
Functions and Graphs
Module 2 · 2 Hours to complete
Measuring Rates of Change
Module 3 · 3 Hours to complete
Introduction to Probability Theory
Module 4 · 3 Hours to complete
Fee Structure
Payment options
Financial Aid
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Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
Frequently asked Questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.






