Zurück zu Data Science Math Skills

Sterne

9,893 Bewertungen

•

2,231 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!...

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)

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!

Filtern nach:

von Maria S

•19. Feb. 2020

I found the first two.5 modules very well done. However, the second half of week three and week four were very poorly done. I am still uncertain about the applications of Bayes' theorem and the combination/permutation concepts. I had a very difficult time with the last quiz and had to go elsewhere to actually learn what I needed to, and even so, I still do not understand the approach to solving some of the problems. Quite frustrating and not rewarding.

von Donna C

•16. Nov. 2020

While this was a good basic math, probability, and statistics refresher with good background material and reference documentation, it only scratches the surface of data science. I did like the problem solving style and the set theory this course encouraged, I did not find it sufficient to call a "data science" class. I understand this is may be a course prerequisite for other course, but alone I don't think it should refer to "data science".

von christopher w

•25. Feb. 2018

The first two weeks were well paced, in week 3 I think too much is covered too quickly and in week 4 there is a further acceleration. That said, the course was good in highlighting the areas that I feel I need to work on and motivated me to take University of Zurich's intro to probability which filled the gap for the content from week 4 here. I think this might be a good refresher course for someone whose knowledge is not too stale.

von A. S

•10. Feb. 2021

I would give it a 3.5. Good for introducing you to the concepts you might need, but very bad at explaining them. It is understandable since it is a short course. Just bear that in mind when you enroll, if you want to explore a concept in depth you will need to look elsewhere. My main concern lies in the fact that the test were slightly harder than the topics covered on the videos, but still in the realm of manageable.

von Dan H

•18. Feb. 2019

good subject matter choice; however, quality varied between the two professors. weeks 1-3 provided good clear lectures and enough practice questions; but week 4 had several confusing points in the lecture, then not enough practice. I really had to supplement my learning with outside videos and problems for week 4. but i passed the final test first time. thanks for narrowing down the maths needed for data science.

von Marcos G

•4. Nov. 2021

The final week, covering Probability, was pretty mediocre. A very strong weeks 1 and 2 start with a pretty steep decline towards the end. I picked up this course as a demonstration of core data science math skills. I already knew most of the concepts so I didn't have much difficulty, however, if you're looking to pick this course up purely to acquire these new skills, I'd suggest looking elsewhere.

von Patrycja J

•12. Mai 2020

Lessons 1-3 are ok. Everything is explained well and you can make the tests easily. 4 is very difficult and despite many trials, I was not able to make it. And because of chapter 4 I suggest you rather take another course.

There is also a technical problem, because the formulas are displayed in java script, so it is not easy to understand how the formula looks like, if you do not know the script :(

von Phyllicia A M B

•19. Juni 2020

The lectures are very short and simple. Sometimes the explanations are not explained thoroughly. Students without background on the subject will find it difficult to apply the concepts in actual problems like in the quizzes. I hope you can improve your content, discussions, and quizzes so students without background in advance math can enjoy your course. Thank you!

von Sina P

•18. Mai 2021

The course was useful and well designed. Trainees can achieve a noticeable background of data science and gain a good vision about what data science is. However, It would make the course more comprehensive if the trainers provide some real life example questions especially when talking about the mathematical rules and formulas during the course.

von Brannon C

•11. Mai 2020

Helpful overview and review if it’s been a while since you taken stats and probability. But really needs more practice problems with explanations to practice through the workflow on the last two weeks. The formulas and calculations get pretty intense. They have printable handouts that go with all videos that were very helpful.

von Raymond S

•21. Sep. 2019

Keep in mind that this is meant to be an introduction to some of the math topics used in data science, it is not a comprehensive course. The course needs to include worksheets with practice problems for the students to practice. The instructors do not use enough real-world examples to demonstrate how the theory is applied.

von ACHRAF T

•25. Apr. 2020

je pense qu'il manque quelque définitions ,par exemple , pour dire que la probabilité d'un événement est égal à la somme de probabilités d'intersections de cet événement avec d'autres ,mais en fait on peut dire cela sauf si les autres événements forment un système complet d'événements. mais en général ça reste utile .

von SAYAN B

•18. Apr. 2020

The course videos for the topics for Week 3 and 4 are not well explained. Even some of the questions in the quiz are not written in proper format. Please look into this and make changes to the course. Otherwise the syllabus of the course is well designed and the probability questions are of quite high standard!

von Jeffrey A B

•22. Juni 2019

Felt like the first 3 weeks were pretty good but the probability section needs a lot more detailed explanations and examples to make the information clear. For those that are already OK with this subject, it's probably fine but for those that haven't had much background in probability, this part was lacking.

von Jennifer H

•11. Juli 2021

The math went from extremely easy in weeks 1-3, to very challenging (with insufficient explanations) in week 4. I watched the videos from weeks 1-3 on 1.5x speed, but even going back to normal speed for week 4 was not enough. I had to find external resources to provide additional explanations for week 4.

von Scott M

•16. Aug. 2020

The first half was planned and organized. The second half seemed haphazard. Examples were a little hard to follow. Quizzes were fine and seemed to test the material presented. I have only taken three other courses (4 total) and this one seemed a little rushed and the second half was created on a whim.

von Danilo C

•17. Jan. 2018

First 2 weeks of the course is amazing, very good didactics. The second teacher does not use very good examples, and the thing starts to fill like old math classes, but overall is good. I will need to redo the last 2 weeks because i fill that I will not remember most of it so easy as the first 2 weeks.

von Saurabh K

•27. Mai 2018

Good for high level understanding of few of the concepts. But last week 4 tutorials are covered at very high level , it was quite difficult to understand probability topic without referring to other online tutorials. I wish more examples could be given in the tutorials to strengthen understanding.

von Margaret S

•25. Juli 2017

The class is good. However, the second half of the class zips through concepts that need a lot more explanation than is provided. Moreover this class would benefit from an optional tutorial on how to input factorials into a calculator as the answers on the exam go to the 8th decimal place.

von Glory J

•6. Juni 2021

The course was okay. Some fundamentals like logarithms was clear to me. However, they did not do a very good job in explaining the probability section like Bayes' conditional probability and binomial theorem in a clear and concise way like it was done with the other topics

von Nicolás M

•3. Mai 2021

While it is a good course overall, and the first three modules are excellent, the final module on probability has poor explanations. To understand and complete this module I had to review other sites and come back, following recommendations from many other students.

von Elizabeth C

•14. Jan. 2021

Didn't like it. It helped me cover some of the concepts I have to know as an aspiring data scientist and the problems are good though tricky, but the explanations were confusing. I often find myself watching Khan Academy videos then coming back to do the questions.

von Aasiya S

•28. Juli 2021

The course could have been better, since majority concepts were not explained elaborately especially module 4. Will not recommend if you really want to learn something. Tests and assignments were good as they were not direct questions but based on application.

von Taruna J

•6. Aug. 2020

Some concepts have been explained beautifully, which made things easier to understand. Some concepts (probability) I earlier understood so very well, but now I am confused with the teachings from this course. I don't really like how it has been explained.

von Nitikorn S

•22. Mai 2020

The first half is really well explained. However, the second part could be improved with a more detailed explanation rather than introducing the equation and jump straight to the problem. Also, I think the quizzes in the latter part are (too) difficult.

- 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