What you will learn in the Data Science Math Skills Course
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Understand set theory, including Venn diagrams and set operations.
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Learn properties of the real number line and interval notation.
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Apply summation and sigma notation in mathematical expressions.
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Master graphing on the Cartesian plane, including slope and distance formulas.
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Explore functions and their inverses, and understand instantaneous rate of change.
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Study exponents, logarithms, and the natural logarithm function.
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Grasp basic probability theory, including Bayes’ theorem.
Program Overview
Welcome to Data Science Math Skills
⏳ 22 minutes
- Overview of the course structure, working process, and information about course certificates, quizzes, video lectures, and other important course details.
Building Blocks for Problem Solving
⏳ 3 hours
- Introduction to set theory, real number line properties, interval notation, and summation notation.
Functions and Graphs
⏳ 3 hours
- Exploration of the Cartesian plane, slope and distance formulas, and graphing functions and their inverses.
Measuring Rates of Change
⏳ 3 hours
- Understanding instantaneous rate of change, tangent lines, exponents, logarithms, and the natural log function.
Introduction to Probability Theory
⏳ 3 hours
- Basic probability theory, including Bayes’ theorem and its applications.
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Job Outlook
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Enhances foundational math skills essential for data science roles.
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Provides a solid foundation for advanced studies in data analysis and machine learning.
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Completing this course can bolster qualifications for roles requiring strong mathematical and analytical skills.
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Related Courses
- Mathematical Thinking in Computer Science Course – Develop structured thinking and problem-solving skills essential for algorithms, data structures, and data science workflows.
- Introduction to Discrete Mathematics for Computer Science Specialization Course – Build a strong foundation in logic, sets, graphs, and combinatorics that supports data science and computational modeling.
- Mathematics for Machine Learning and Data Science Specialization Course – Learn the core mathematical concepts required for machine learning, including linear algebra, probability, and calculus.
Related Reading
Gain deeper insight into how mathematical skills translate into practical data science work:
- What Is Python Used For? – Understand how Python applies mathematical concepts to data analysis, modeling, machine learning, and scientific computing.
