Zurück zu Data Science Math Skills

Sterne

10,208 Bewertungen

•

2,280 Bewertungen

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.
Learners who complete this course will master the vocabulary, notation, concepts, and algebra rules that all data scientists must 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 summation and Sigma notation
~Math on the Cartesian (x,y) plane, slope and distance formulas
~Graphing and describing functions and their inverses on the x-y plane,
~The concept of instantaneous rate of change and tangent lines to a curve
~Exponents, logarithms, and the natural log function.
~Probability theory, including Bayes’ theorem.
While this course is intended as a general introduction to the math skills needed for data science, it can be considered a prerequisite for learners interested in the course, "Mastering Data Analysis in Excel," which is part of the Excel to MySQL Data Science Specialization. Learners who master Data Science Math Skills will be fully prepared for success with the more advanced math concepts introduced in "Mastering Data Analysis in Excel."
Good luck and we hope you enjoy the course!...

VS

22. Sep. 2020

This course syllabus is great. It starts wonderfully. Week 1 to 4 is taught by Paul Bendich, and Daniel Egger the instruction is awesome. Effective way to refresh and add the Data Science math skills!

VC

16. 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)

Filtern nach:

von Murali M A

•27. Aug. 2017

Succinct explanation of the basics. Take more time at the Bayes theorem. It is worth it. Work out all the problems and keep reading the PDF notes accompanied with the videos. All in all, a great experience for those who have missed some basic math in earlier education. I am onward to my next course in machine learning and data science. Cheers

von Avinaash

•18. Feb. 2021

I had a lot of forgotten knowledge from when i was at university which this course really helped refresh me in. I think its a really good course for a refresh or even a beginner however at times I felt a few things were too quickly glanced over when deriving formulas which made it sometime a challenge to follow but overall was a good course.

von CJay

•13. Juni 2020

This is a very good course for those who have forgotten about their math skills and are new to data science. The first few weeks will cover basic math which you can skim through if you are good in math. This course also introduces you to statistics in particular Bayes' theorem which is an important topic of data science. Enjoy the course!

von Gitashah

•31. Jan. 2019

First of all thanks to the data science math skill because i learned many new things,ideas,knowledge and skills from this course and more thankful to professors because of them i am able to give all the answers and it was too much interesting to do .

Thanks to all the teams of coursera as well as to the data science math skill......

von Shahriar H

•14. Feb. 2022

Hello to everyone on Coursera I just finished this course and I definitely learned a lot! I learned all of these back in high school but after a few years of not studying math, I forgot most parts. The course is well structured and is explained in a simple and easy to understand manner. and The video companions help a lot. Thanks

von Garth Z

•10. März 2017

If you are a right-brainer and/or rusty on math, I strongly recommend this course as a precursor to Duke's Intro to Probability and Data course. Some of the practice and final quiz questions really threw me (and that's good)... Most of them I was able to rethink and derive the correct answer and a few others remain a mystery... :-)

von Deleted A

•22. Jan. 2017

I loved this class, the only one of it's kind and much needed, unless you particularly want to re-do your long forgotten high school and college math. It was nice seeing a Venn diagram again. I did have to supplement some of the material that was covered quickly with google searches, but filling in the blanks was quick and easy.

von Ramesh K

•18. Juli 2020

It is a thoughtful and well-designed course. I really enjoyed learning the core math skills related to data science. As a starter on data science as a field of study and career, the course refreshed my previous knowledge and helped me learn more about the mathematical skills needed for learning and practicing data science.

von Ankur A

•18. Apr. 2018

Hi. A very good refresher course that serves as a pre-requisite to Machine Learning and Data Science courses. Probability could have been a little better explained, specially the processes and event part. I would also like to see Vectors and Matrices added to this course, which is equally vital for Data Science.

von Bernardino R

•20. Mai 2020

This course provided clear, expert teaching at a very good pace. The materials were very helpful & directly applicable. The videos were well portioned, and the professors are well spoken & highly competent. I highly recommend Coursera, these professors & this course. I plan on pursuing more in this subject.

von Iain S

•4. Apr. 2021

Everything was going fine for me until I got to the statistics portion. This is something I've struggled with before, so I can't blame the course for struggling again here, but I would have preferred more learning content for week 4, perhaps even splitting it into 2 weeks to make it a 5 week course in total.

von Preeti A

•31. Jan. 2019

Learning this course I have gain many new and interesting skills. I am very much glad to get the knowledge from two professors and they gives me more knowledge on those interesting courses. I was able to do the answers of the given courses.And I THANKS them to give me such opportunity to do these courses.

von Armine

•4. Apr. 2018

Everything was great except probability theory. The videos were hard to follow and understand because everything was a kind of mess. Reading materials would be much better for probability section. Overall it was very helpful for me and I am very grateful for this wonderful course!!!

von Iman S

•16. Apr. 2020

The course is completely related to prerequisite data science skills. There are lots of useful materials. However, the last module (probability) is kind of introduction and superficial, and do not discuss probabilities concepts and distributions in depth.

In general, the course is Great

von Olga E F C

•14. Apr. 2021

Fue un curso muy útil para retomar los temas de funciones y probabilidad, a mi me costó más comprender los temas de la semana 4, por lo que recomiendo busquen otros ejemplos para seguir practicando. La gran ventaja es que puedes consultar los materiales tantas veces como lo necesites.

von Mahyar

•22. Aug. 2017

Good course because it focuses on basic statistical science needed in Data Science. Only issue I had with this course was it was pretty short. Shorter than I thought by looking at the syllabus. Also the agenda is very simple in the first couple of weeks until it gets to the last week.

von Subhadip D

•26. Juli 2020

Would have been better if real-time tool were used such as PTC Math-cad or Mathworks Matlab then the Simulation based learning approach could have been much better. Well this course has vas potential and can be be released as series with capstone simulation project. I loved it though

von Rahul K

•29. Apr. 2020

very nice, this course helps me a lot for a basic understanding of the different concept of math. The course is also design in very well manner for understanding each and every concept clearly.i also very thankful to the teacher association who created this course for helping me.

von Muhammed B K

•5. Okt. 2020

Great course for starters. For first three weeks there can be some advanced examples as extras and for the last week, it would be better if several complex examples solved by instructors since Bayes and Conditional probability can be confusing sometimes. Thanks for the course.

von Rajat P T

•20. Juli 2020

The course explained all the basic mathematical concepts really well, especially Bayes' theorem and probability theory.The best thing that I liked about this course is that it also explained some simple real world test scenarios where these mathematical concepts can be used.

von Priti B

•28. Mai 2019

I came for this course after working on data science for sometime. While initial 2 weeks were easy and known, last 2 weeks were really helpful. My probability concepts become much clearer after going through the lecture and tests. Very precise and clear course. Thanks a lot!

von Pavel A

•14. Nov. 2021

Thank you for your work and for free access to the course. It was very helpful for my university Machine Learning course. After completing the course I want to notice the following: - course is siutable almost for evevryone - highly qualified teachers - good visual support

von Christopher C M

•5. Mai 2022

As a fellow educator found this course to be very helpful. Could like to see an area, and maybe I just didn't look hard enough for it that had some more practice problems to hone some of these skills. Especially the probablity towards the end with Bayes Thrm.

Thank you

von Adnaeva G S

•15. Okt. 2020

Effective way to refresh and add the Data Science math skills! Thanks a lot! 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.

von James T

•2. Apr. 2018

Everything I've tried diving into in regards to data science after having been out of school for a while (I'm 34) has been stuff I haven't learned or forgot. This course was perfect. Nothing was too difficult for someone who still remembers basic math and I learned a lot.

- Google Data Analyst
- Google-Projektmanagement
- Google-UX-Design
- Google IT-Support
- IBM Datenverarbeitung
- IBM Data Analyst
- IBM-Datenanalyse mit Excel und R
- IBM Cybersecurity Analyst
- IBM Data Engineering
- IBM Full Stack-Cloudentwickler
- Facebook Social Media Marketing
- Facebook Marketinganalyse
- Salesforce Sales Development Representative
- Sales Operations in Salesforce
- Buchhaltung mit Intuit
- Vorbereitung auf die Google Cloud-Zertifizierung: Cloud Architect
- Vorbereitung auf die Google Cloud-Zertifizierung: Cloud Data Engineer
- Eine Karriere starten
- Auf eine Zertifizierung vorbereiten
- Bringen Sie Ihre Karriere voran

- Kostenlose Kurse
- Lernen Sie eine Sprache
- Python
- Java
- Webdesign
- SQL
- Gratiskurse
- Microsoft Excel
- Projektmanagement
- Cybersicherheit
- Personalwesen
- Kostenlose Kurse in Datenverarbeitung
- Englisch sprechen
- Inhalte verfassen
- Full-Stack-Webentwicklung
- Künstliche Intelligenz
- C-Programmierung
- Kommunikationsfähigkeiten
- Blockchain
- Alle Kurse anzeigen

- Kompetenzen für Datenwissenschaftsteams
- Datengestützte Entscheidungsfindung
- Kompetenzen im Bereich Software Engineering
- Soft Skills für Ingenieurteams
- Management-Kompetenzen
- Marketing-Kompetenzen
- Kompetenzen für Vertriebsteams
- Produktmanager-Kompetenzen
- Kompetenzen im Bereich Finanzen
- Beliebte Kurse in Datenverarbeitung im Vereinigten Königreich
- Beliebte Technologiekurse in Deutschland
- Beliebte Zertifizierungen für Cybersicherheit
- Beliebte IT-Zertifizierungen
- Beliebte SQL-Zertifizierungen
- Karriereleitfaden für Marketing-Manager
- Karriereleitfaden für Projektmanager
- Python-Programmierkenntnisse
- Karriereleitfaden für Webentwickler
- Datenanalysefähigkeiten
- Kompetenzen für UX-Designer

- MasterTrack® Certificates
- Zertifikate über berufliche Qualifikation
- Universitätszertifikate
- MBA- und Business-Abschlüsse
- Abschlüsse in Data Science
- Abschlüsse in Informatik
- Abschlüsse in Datenanalyse
- Abschlüsse im Gesundheitswesen
- Abschlüsse in Sozialwissenschaften
- Management-Abschlüsse
- Abschlüsse von europäischen Spitzenuniversitäten
- Masterabschlüsse
- Bachelorabschlüsse
- Studiengänge mit Performance Pathway
- BSc-Kurse
- Was ist ein Bachelorabschluss?
- Wie lange dauert ein Masterstudium?
- Lohnt sich ein Online-MBA?
- 7 Finanzierungsmöglichkeiten für die Graduate School
- Alle Zertifikate anzeigen