Zurück zu Data Science Math Skills

Sterne

9,593 Bewertungen

•

2,179 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!...

AS

11. Jan. 2019

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)

RS

5. 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.\n\nThank you for a great class!!

Filtern nach:

von Hugh J

•27. Sep. 2020

Needs more statistics

von Elvin G

•19. Okt. 2018

It is too low level

von Korkrid A

•27. Apr. 2018

Good for beginners.

von Vikas G

•17. Juni 2020

Fantastic teaching

von PARDESHI R H

•17. Mai 2020

Very useful course

von Shanmuga P

•23. Feb. 2018

Good!!

von MUTHU A P S

•7. Juni 2020

good

von ChiangSheng L

•23. Aug. 2021

Actually the lessons from first three weeks are really basic (junior to senior high level), and sometimes I can't find any strong relationship with data science. And the fourth week is about probability theorem including the marginal/joint probability and bayesian theory without introducing other fundamental concepts, which could make the student quite confused sometimes.

There are several typos by the first teacher, which most are all corrected but quite disturbing. And the handwriting of the second professor is sometimes sloppy. I'd rather check the "video companion" before taking the class. BTW, they are really good and concise to summarize the concept and understand what the professors are talking about.

About the quiz/exam, most are good with explanations. But a lot of question require electronic calculator. Some question do not provide basic value of number like log(2) or which is quite annoying.

It's not good as imagine, but it does not take much time to finish.

von Carolin K S

•21. Juli 2020

This class fails to give a single explanation as to how the math skills will apply to data science. The first three weeks are a nice basic explanation of some of the math that will be needed. If you haven't done coding before or have some background in coding, you will have no idea where this class is going to be applied. The fourth week is the worst explanation of probability you can imagine -- opaque derivations and almost no explanations. I do not recommend this class as it fails to address the "why" of the title -- how does math apply to data science.

von Dennis F

•15. Mai 2021

i passed all quizzes and exams at 100% most of them in one try.

presentations were a bit sloppy, and often i found i understood the concepts, but not how they were presented.

I did learn things from the course, but the experience could have been a lot better

especially week 4 was problematic, the bayesian probability and inverse probability was hard to understand from the videos or the notes alone, or in combination.

notes for one of the video had only notes for about the first half of the video, so no notes for the rest.

von Mike S

•18. März 2021

The content is OK; the execution isn't quite ready. Most is fairly basic, but is necessary and potentially a good review. But the course comes across like a first draft. Mistakes in videos are not re-recorded, but called out with a disclaimer. I believe there are two errors in answers to practices and quizzes, but it's possibly my own mistake on one. I noticed one instance where the correct answer is in a different font than incorrect answers. Overall, OK content but not very polished. It could use a second revision.

von Borja C

•10. Sep. 2020

The first 3 weeks are quite good... but then it makes a gigantic leap on the 4th week. Please update the explanations on Bayes and the examples... they are not optimal. Judging from the comments I have seen, I am not the only one.

Thinking about it, I think maybe it would be worth to spend more time with probability and a bit less with the other stuff or even add another week... definitely probability in one week is a far shot... and it is key to understand data science correctly

von Helene H

•25. Sep. 2020

A pretty good course even if week 3 and 4 are very difficult for beginners.

A few improvements are urgently needed:

-There are mistakes in the quizzes, which mistakes have been pointed out by generations of students for months/years in the forums, but have never been corrected. Such a disgrace and waste of student time!

-Also using Chrome makes you unable to read the formulas, which should be said in the course outset.

von Deepak R

•27. Dez. 2020

At week 4 the course was covered in a rush. This course could have been much better if the instructor could have taken the time out and walked the extra mile to simplify the concepts for a larger audience. I already had previous rigorous treatment of Probability theory hence didn't face many challenges. But I have empathy with students enrolling in this course who don't have prior probability background.

von Yury K

•14. Juli 2020

Course has misleading title. It has no strong connection to data science problems or examples from the field (except confussion matrix). First 3 weeks are simple math. Third one is very brief tour to probability with quite brief explanations which will not be enough for beginners to complete the assignment. There are also errors in the asssigments which I had reported.

I will not recommend it.

von Joel L

•8. Sep. 2020

Instructors were knowledgeable, but I found the lectures to be a theoretical example, followed by a very simple real-life example. Then when you take the quiz, the questions are SIGNIFICANTLY more complicated than what I was ever taught in the lessons. Some worksheets of sample problems that escalate up to the difficulties seen in the quiz would have been very helpful.

von Utsav S

•6. Mai 2020

The course content was very basic. Especially the first part of the course.

The later part(probability) of the course was very theoretical in nature. Typical problems in quizzes and examples as you would find in any mathematics text book. Being Data Science Maths skills course, I was expecting some real life example or even the mention of data science during the course.

von Star S

•13. Juli 2021

The course started of well paced but began to get complex and hard for me to pick up the logic. i clearly had a bad experience especially in probability part. could have used more understandable examples and explanations . although its said that this course is entirely for beginners, i feel its best suited for people who comes to refresh the topics .

von Esdras C

•6. März 2020

After the second week, explanations become too abstract without a concrete explanation of how relates with the real world. Also, the examples are too short compare to the problems that are included in the quizzes. It will be way more interesting to learn the explanation of the quizzes than the abstract examples during the presentations.

von John

•22. Juli 2020

Some useful concepts, but several of them, especially in the last week of the course, were very vague and did not give examples on how to use them to solve problems, which is the point of the course. If i wanted definitions and formulas I can just google them. The whole point of a video is to teach me how to apply it

von Shadman W

•21. Mai 2020

The initial modules are insightful and helpful. But I had a lot of problems going through the material in week 4. The instructor struggles to make the content engaging and the videos often end up sounding very monotone. There's a big gap between the material discussed and the questions asked in practice.

von Jansen M A

•31. Dez. 2020

The course is fairly easy and unchallenging. It's like an introduction in maths for high school students. I was expecting harder maths related to data science and/or machine learning, but this is just a review of high school maths. Not entirely a waste of time, but disappointing.

von TANMAY A

•28. Mai 2020

baye's theorem and the binomial addition to it should have been explained broadly, this is a multi country based program , people from different country access it. hence each and every formulae and colocations should be explained better and write-in a better way.

von Michael Q

•7. Apr. 2017

Very rushed presentation. Blows right through a lot of fundamental concepts without a deep enough explanation or enough practice material (especially in the last two weeks). I feel like completing this class will require supplementation with better instruction.

- 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
- Facebook Social Media Marketing
- IBM Full Stack-Cloudentwickler
- Salesforce Sales Development Representative
- Sales Operations in Salesforce
- Soporte de Tecnologías de la Información de Google
- Certificado profesional de Suporte em TI do Google
- Google IT Automation with Python
- DeepLearning.AI TensorFlow
- Beliebte Zertifizierungen für Cybersicherheit
- Beliebte SQL-Zertifizierungen
- Beliebte IT-Zertifizierungen
- Alle Zertifikate anzeigen

- 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
- Android-Entwicklungsprojekte
- TensorFlow- und Keras-Projekte
- Python für alle
- Deep Learning
- Excel-Kenntnisse für Beruf
- Geschäftsgründungen
- Maschinelles Lernen
- AWS-Grundlagen
- Datenengineering-Grundlagen
- 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 Abschlüsse anzeigen