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.
von
Data Science Math Skills
Duke UniversityÜber diesen Kurs
228.485 kürzliche Aufrufe
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Stufe „Anfänger“
Ca. 13 Stunden zum Abschließen
Englisch
Untertitel: Arabischer Raum, Französisch, Portugiesisch (europäisch), Italienisch, Vietnamesisch, Koreanisch, Deutsch, Russisch, Englisch, Spanisch
Kompetenzen, die Sie erwerben
- Bayes' Theorem
- Bayesian Probability
- Probability
- Probability Theory
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Stufe „Anfänger“
Ca. 13 Stunden zum Abschließen
Englisch
Untertitel: Arabischer Raum, Französisch, Portugiesisch (europäisch), Italienisch, Vietnamesisch, Koreanisch, Deutsch, Russisch, Englisch, Spanisch
von
Duke University
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.
Lehrplan - Was Sie in diesem Kurs lernen werden
18 Minuten zum Abschließen
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 Minuten zum Abschließen
1 Video (Gesamt 3 min), 2 Lektüren
4 Stunden zum Abschließen
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 Stunden zum Abschließen
10 Videos (Gesamt 93 min), 4 Lektüren, 4 Quiz
3 Stunden zum Abschließen
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 Stunden zum Abschließen
8 Videos (Gesamt 72 min), 3 Lektüren, 3 Quiz
3 Stunden zum Abschließen
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 Stunden zum Abschließen
7 Videos (Gesamt 66 min), 3 Lektüren, 3 Quiz
3 Stunden zum Abschließen
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 Stunden zum Abschließen
8 Videos (Gesamt 66 min), 4 Lektüren, 4 Quiz
Bewertungen
- 5 stars63,75 %
- 4 stars28,11 %
- 3 stars5,76 %
- 2 stars1,54 %
- 1 star0,82 %
Top-Bewertungen von DATA SCIENCE MATH SKILLS
von VC16. Mai 2020
Effective way to refresh and add the Data Science math skills! Thanks a lot! At the time of the study some of the quizzes content were not rendering correctly on mobile devices (both iPad and Android)
von PS22. Juli 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.
von RS5. Mai 2020
This was mostly review for me though probability especially Beyes Theorem derivation was new. The instructors provided clear often refreshing ways to look at material.
Thank you for a great class!!
von MG27. März 2018
Please include integration, algorithm analysis (big O, theta, omega), recursion and induction. Your course is helpful, thank you. If you add those things I've mentioned it would be absolute gold.
Häufig gestellte Fragen
Wann erhalte ich Zugang zu den Vorträgen und Aufgaben?
Was bekomme ich, wenn ich das Zertifikat erwerbe?
Ist finanzielle Unterstützung möglich?
Will I receive a transcript from Duke University for completing this course?
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