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Data science courses contain math, not to be avoided! This course is designed to teach students the basic math they will need to be successful in almost any data science math course and was created for students who have basic math skills but may not have taken algebra or pre-calculus. Data Science Math Skills introduces the basic mathematics that data science is built on, without the added complexity, by introducing unfamiliar ideas and mathematical symbols one at a time. Students who complete this course
Data science courses contain math, not to be avoided! This course is designed to teach students the basic math they will need to be successful in almost any data science math course and was created for students who have basic math skills but may not have taken algebra or pre-calculus.
Data Science Math Skills introduces the basic mathematics that data science is built on, without the added complexity, by introducing unfamiliar ideas and mathematical symbols one at a time.
Students who complete this course will master the algebra vocabulary, notation, concepts, and rules that all data scientists should know before moving on to more advanced material.
Topics include: ~ Set theory, including Venn diagrams ~ Properties of the real number line ~ Interval notation and algebra with inequalities ~ Uses for addition and sigma notation ~ Mathematics in the (x,y) plane, slope and distance formulas ~ Graph and describe functions and their inverses in the xy-plane, ~ The concept of instantaneous rate of change and lines tangent to a curve ~ Exponents, logarithms, and the natural logarithmic function.
~ Probability theory, including Bayes' theorem.
While this course is intended as a general introduction to the mathematical skills necessary for data science, it can be considered a prerequisite for students interested in the "Mastering Data Analysis in Excel" course, which is part of the specialization in data science from Excel to MySQL.
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Students who master data science math skills will be fully prepared for success with the more advanced math concepts presented in "Mastering Data Analysis in Excel."
Good luck and we hope you enjoy the course!
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This short module includes an overview of the course structure, work process, and information on course certificates, quizzes, video lectures, and other important course details. Be sure to read it right away and refer to it when needed
This module builds vocabulary for graphing functions on the plane. In the first lesson, "Descartes was really smart", you will get to know the Cartesian plane, measure the distance on it and find the equations of the lines. The second lesson introduces the idea of a function as an input-output machine, shows you how to graph functions on the coordinate plane, and reviews important vocabulary.
This module begins with a very gentle introduction to the concept of derivative calculus. The first lesson, "This Is About the Derived Stuff," will give you basic definitions, work through some examples, and show you how to apply these concepts to a real-world optimization problem. We then move on to exponents and logarithms, and explain the rules and notation for these mathematical tools. Finally, we learn about the rate of change of continuous growth and the special constant known as "e" that captures this concept in a single number, about 3.
This module introduces the vocabulary and notation of probability theory: mathematics for the study of outcomes that are uncertain but have predictable rates of occurrence. We start with the basic definitions and rules of probability, including the probability of two or more events occurring, the addition rule, and the product rule, and then proceed to Bayes's Theorem and how it is used in practical problems.
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