Retour à Data Science Math Skills

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10,918 évaluations

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)

AS

11 janv. 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)

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par Christopher B

•6 juil. 2020

The course has truly been helpful in showing me my level of understanding on the topics, as like all the other reviews it was a great refresher and more so it was truly helpful in helping me see areas i needed to improve on to become more advance in mathematics. i definitely recommend this course for those who want an understanding of the mathematics that is used in data science. this course by no means is an all you need math course to be successful with data science, but more of a stepping to stone or guide in my opinion in finding the right path to take to become far better in mathematics for this field.

par Mariana E

•8 avr. 2018

Este curso lo recomiendo mucho a quienes estén interesados en refrescar sus conocimientos de matemáticas para pasar a cursos de estadística o data science. Es muy compacto por lo que los temas se tratan de manera concisa, pero realmente se avanza si se invierte el tiempo necesario. Yo estoy interesada en la estadística y mi campo es la lingüística, así que me tocó trabajar muchas horas haciendo cuentas en el papel y en la calculadora, buscando cómo hacer para sacar las distribuciones binomiales y las funciones básicas, pero me pareció al final que he dado grandes avances, me encantan las matemáticas.

par Laurent B

•19 juin 2017

While most of material is well known, it is presented in a great way, so it is a clean and smart refresher for Sets, basic Algebra and notations, Cartesian geometry and functions, and derivatives. I knew the material about logarithms, exponentials and probabilities, but I felt that I knew it better in the end of this courses. Material is great, and teachers are very clear. I wish they came with more material about calculus (matrices), vector spaces, Lagrangian, Hessian and so on, which are also really interesting in Data Sciences.

par Aditya K

•21 sept. 2017

This course offers a great refresher of the FUNDAMENTALS of Linear Algebra , Calculus and Probability.

Do note the strong emphasis on fundamentals.

All lectures are well produced and the material put forward in an unambiguous and layman language.

The concepts presented are very easy to grasp , all thanks to the brilliant efforts of professor Bendich and professor Egger.

This course , along with another course on Calculus would serve as a great starting point for all data science enthusiasts and I strongly recommend it to everyone.

par Michelle C d J

•14 mai 2021

I found the first half of the course quite easy, as it was a refresher on the math that I managed to learn and retain as a high school student. However as I progressed through the course and found myself revisiting calculus and statistics concepts I found it challenging as I hadn't so much as touched a mathematics textbook since I graduated from university. That said I found this course excellent at understanding the mathematical principles on which data science foundations are built. It's definitely worth taking in my opinion.

par Ginger d R

•23 sept. 2022

This course was great! The first two weeks are relatively easy, but during weeks 3 & 4 you're going to have to watch some youtube videos on natural logs & probability. I recommend videos by StatQuest & the organic chemistry tutor.

I've found that this is true for any course that is modestly challenging, so it didn't really bother me much. I would have liked a few more videos of the teacher solving some example problems, but since there are thousands of examples of this on youtube, you shouldn't get stuck on any quizzes.

par Josmy A J

•25 oct. 2020

I learned a lot through this course. Set Theory,it's applications ,many formulas,functions,graphs ,probability and it's applications etc etc..I was able to study everything very well.Teachers taught well.it was a good course and also a good experience.I was able to know a lot of things. It was a kind of class where everything could be understood. The teachers explained everything very well.The examples given was more helpful.Through this course I was able to do each problem better.Thanks to the teachers who taught.

par Baskaran V

•15 janv. 2017

One of the best course, i have ever learnt. Even though i have been learning the Data Science for the last few years, i had no idea how the algorithms are working in technical. Which i was always skeptical. But honestly, now i am able to get things really faster than before. I am very happy, i have joined this course. Thank you so much for coursera to bring this course and importantly thank you so much for the professors to explain things in an easy for the people to understand. God bless you both and your family.

par Abhijit D

•17 avr. 2020

I thoroughly enjoyed taking this course because of the effective syllabus that reviews the math skills for Data Science. I liked having both Test and Graded Quiz to check the understandings of the subject.

Test Quiz gives good feedback on both correct and incorrect answer that helps to compare the problem-solving strategy and solution of the students with the correct solution.

Graded Quiz gradually becomes more challenging and the week 4 graded quiz is the most challenging quiz of all the graded quizzes.

par Sanjai S

•15 mai 2020

I enjoyed the course content and lectures. The quizzes were a good test of understanding. I was wondering if there could have been a few more additional lectures and practice problems on probability. I request the team to check the answer to the 11th question on the last quiz of week 4.

Prof. Egger's lectures were very interesting and I only wish he had a larger writing board or apparatus. Thank you for getting me interested in a subject that is not my core area of work!

par Anurag G

•11 juil. 2020

It was exactly what it said, math skills for the Data Science. Standard of problems kept increasing and became more and more challenging. I was able to finish the first 3 weeks in one day, because of my physics masters, I had previous Maths training, and that came handy. For the fourth week, the probability was extremely useful and challenging. I would recommend this to all future data scientist, especially if you are not coming from the Physical science background.

par Kianti S

•3 juil. 2020

The learnings are very broad meaning, it is not only applicable in the field of data analytics but also in a the filed of mathematics, sciences, and statistics in my opinion. Thank you professor Daniel Egger and professor Paul Bendich for the amazing efforts, like for the amazing lectures and putting the step by step process of how to solve certain problems in your quizzes and also the of copies of the handouts which made my learning more conviniet.

par Mario C

•11 juin 2020

I never thought I could do math, that I just didn't get it. In this course I was doing math stuff that I considered was way above me. While I still have some difficulties with the more advanced concepts such as logs and "where to begin" with probabilities, I still have a foundation in these that I actually understand. Knowing my inadequacies I can go on and study those, but thank you so much for making an easily understandable course.

par Ronald B

•8 août 2021

This course help me understand Probability. Highly recommended. It starts easy, which is only means it capture a lot of basic mathematics terms and ensure you adverse to it, and toward the end and even each time it gave you appropriate tools to in depth understand the fundamental of each terms. And o' ya it give you the equations and example to work on simple yet fundamental math equations to test your understanding. Good course.

par Yuanita S

•26 mai 2021

I truly enjoyed the course! It is a good refresher and the materials are very straightforward as they cover the maths needed to begin our journey into the basics of machine learning. Videos are short, which I really appreciate! Instructors' handwritings were easy to read an the quizzes were also enjoyable (I'd personally rate the difficulty level of the quizzes around beginner to intermediate, so they are definitely doable).

par Krishnendu S

•26 juil. 2020

Excellent course for beginners. It starts from the basics and goes up to the intermediate level. Excellent short and very well explained videos and exceptionally good practice and graded questions. These questions help students to think deep into the matter and provide the necessary stimuli of in-depth learning. Great course. I am much obliged to Coursera, Duke University and the instructors for giving such an opportunity.

par Artiom C

•26 avr. 2020

From 3 courses I've taken so far, this one was the best, because it covers a lot from basics to complex math. By the end of the course it does try to cover very complicated topics, which if you don't have training in, you will feel the need to supplement from another resources, even though the reading section of this course helps a lot. Lectures on Khan academy were also very helpful in remembering lost concepts.

par Deleted A

•4 déc. 2020

100 OUT OF 100 BECAUSE VIDEOS ARE AVAILABLE WITH GOOD QUALITIES + CONTENT AND EXAMPLES + RESOURCES MATERIAL i.e. THE PDFS ARE AVAILABLE WITH THIS COURSE MATERIALS FOR WHICH NO USE OF HANDWRITTEN NOTES IS REQUIRED .

THANKS A LOT MY ALL DEAR RESPECTED SIR + SPECIAL THANKS TO ALL FACULTY MEMBERS OF DUKE UNIVERSITY FOR THIS MATERIAL PROVIDING TO US

par Laida L

•19 avr. 2020

The course was easy and comprehensible as long as you have done basic maths at some point in your life. For those who don't I would suggest to go and take a calculus and statistics course and revisit. Otherwise, you would have to do some research by your own, in order to be able to follow. Keep in mind that if you do not see the exponents etc, change browser. Chrome seems to work better than my Firefox.

par Oleh L

•30 déc. 2022

Thank you very much for creating such a useful course. Now I'm better at math and data science. During the course, I remembered some mathematical topics and learned what topics are used in data science. All lectures are well structured. Well-composed additional materials for lectures help when you do not understand everything from the lesson. In general, the course made a positive impression on me.

par Sofia M

•5 sept. 2020

I did learn this course due to I found out a mention about it in an article on the Web. I had 3 higher eds with math, and I needed to get it again because I started to learn Data Science in Health Care Administration. Thanks to the lecturer, thanks to all who made this course availible online.I would like to continue with you! Highly recommend this course for those who need to study Data Science.

par Deleted A

•17 sept. 2020

Great course to strengthen the basics before jumping into applicable approach on data science. The hardest part on this course is the week 4, the one with probability and bayes theorem, and it is advised to get supplementary information on bayes theorem and probability to avoid confusion. All in all, it is highly recommended to anyone starting to learn for solid understanding on data.

par Deleted A

•30 déc. 2020

Overall this course I believe is deliver skill effectively. As I have forgot what is learned in high school due to lack of use in my life after come out from school, the Algebra session is very interesting and easy to learn for me Come to Probability session which is a totally new interesting field to me, I wish I have a better memory because it is not easy to learn in a short time.

par Abdulla A

•10 avr. 2020

I am fairly new to the field of Data Science and Machine Learning, and I felt like i had to strengthen my math skills, hence why I enrolled in the class. The professor did a great job explaining everything in detail, and brushing up on simple math terms. I feel more confident now to move forward into data science that I have a basic knowledge and understanding of the math concepts.

par Tim H

•3 sept. 2020

A fantastic primer on the basics of math related to practically every quantitative field. I hadn't touched probability since high school but now i feel that i am prepared to tackle intermediate probability problems. That being said, prepare to breeze through most of this course and then suddenly find yourself looking up advice on math stack exchange.

I love Bayesian statistics.

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