Data science courses contain math—no avoiding that! This course is designed to teach learners the basic math you will need in order to be successful in almost any data science math course and was created for learners who have basic math skills but may not have taken algebra or pre-calculus. Data Science Math Skills introduces the core math that data science is built upon, with no extra complexity, introducing unfamiliar ideas and math symbols one-at-a-time.
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Data Science Math Skills
Université DukeÀ propos de ce cours
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Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
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Niveau débutant
Approx. 13 heures pour terminer
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Sous-titres : Arabe, Français, Portugais (européen), Italien, Vietnamien, Coréen, Allemand, Russe, Anglais, Espagnol
Compétences que vous acquerrez
- Bayes' Theorem
- Bayesian Probability
- Probability
- Probability Theory
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Niveau débutant
Approx. 13 heures pour terminer
Anglais
Sous-titres : Arabe, Français, Portugais (européen), Italien, Vietnamien, Coréen, Allemand, Russe, Anglais, Espagnol
Offert par
Université Duke
Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world.
Programme de cours : ce que vous apprendrez dans ce cours
18 minutes pour terminer
Welcome to Data Science Math Skills
This short module includes an overview of the course's structure, working process, and information about course certificates, quizzes, video lectures, and other important course details. Make sure to read it right away and refer back to it whenever needed
18 minutes pour terminer
1 vidéo (Total 3 min), 2 lectures
4 heures pour terminer
Building Blocks for Problem Solving
This module contains three lessons that are build to basic math vocabulary. The first lesson, "Sets and What They’re Good For," walks you through the basic notions of set theory, including unions, intersections, and cardinality. It also gives a real-world application to medical testing. The second lesson, "The Infinite World of Real Numbers," explains notation we use to discuss intervals on the real number line. The module concludes with the third lesson, "That Jagged S Symbol," where you will learn how to compactly express a long series of additions and use this skill to define statistical quantities like mean and variance.
4 heures pour terminer
10 vidéos (Total 93 min), 4 lectures, 4 quiz
3 heures pour terminer
Functions and Graphs
This module builds vocabulary for graphing functions in the plane. In the first lesson, "Descartes Was Really Smart," you will get to know the Cartesian Plane, measure distance in it, and find the equations of lines. The second lesson introduces the idea of a function as an input-output machine, shows you how to graph functions in the Cartesian Plane, and goes over important vocabulary.
3 heures pour terminer
8 vidéos (Total 72 min), 3 lectures, 3 quiz
3 heures pour terminer
Measuring Rates of Change
This module begins a very gentle introduction to the calculus concept of the derivative. The first lesson, "This is About the Derivative Stuff," will give basic definitions, work a few examples, and show you how to apply these concepts to the real-world problem of optimization. We then turn to exponents and logarithms, and explain the rules and notation for these math 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—near 2.718.
3 heures pour terminer
7 vidéos (Total 66 min), 3 lectures, 3 quiz
3 heures pour terminer
Introduction to Probability Theory
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.
3 heures pour terminer
8 vidéos (Total 66 min), 4 lectures, 4 quiz
Avis
- 5 stars63,74 %
- 4 stars28,09 %
- 3 stars5,77 %
- 2 stars1,56 %
- 1 star0,82 %
Meilleurs avis pour DATA SCIENCE MATH SKILLS
par PS22 juil. 2017
This is neat little course to revise math fundamentals. I generally find learning probability a little tricky. This course helped me a lot in better understanding Bayes Theorem. Thank you professors.
par NE3 janv. 2021
I want to thank my educators for this wonderful job that they are doing.i have learn so much from you guys and i want to thank you all for your kind support in this data science maths skills.
par AA18 oct. 2020
This is a great course, many things are basic but I have learned those a long day ago. Some explanations are from different perspective than conventional. However, definitely a great course.
par SP29 mai 2020
Great refresher and primer. The section on Probability and Bayes Theory needs a lot more support material (video and notes) as it can get tricky and abstract, especially when doing the quizzes.
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