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Data Science Math Skills

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!

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Rating 4.3★ based on 491 ratings
Length 5 weeks
Effort Four weeks, 3-5 hours per week.
Starts Jul 17 (40 weeks ago)
Cost $49
From Duke University, University of Geneva via Coursera
Instructors Daniel Egger, Paul Bendich, Tina Ambos, Gilbert Probst, Lea Stadtler, Bruce Jenks, Stephan Mergenthaler, Julian Fleet, Cassandra Quintanilla, Claudia Gonzalez Romo, Sebastian Buckup
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science Business Mathematics
Tags Data Science Data Analysis Business Math And Logic Leadership And Management

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What people are saying

last week

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.

It seemed the last week course was a bit rushed and could have been extended into few more classes.

great introduction and refresher to maths skills last week was very hard This course was very good.

Also the agenda is very simple in the first couple of weeks until it gets to the last week.

last week is not good at all i didn't get it all Good materials.

the very last week was toughbeginner of data science will not understand.

First 3 weeks were easy going and the last week was a bit more challenging.

the lectures of last week r very bad Good refresher course with all basic concepts explained very well Awesome course, Thank you!

A useful getting-up-to-speed maths course for those going in to data science the course was great but the last week was so hard and the instructor didn't explain the subject well

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data science math

A great fast introduction into Data Science Math Skills.

It had better if you design a Data Science Math Skills specialization.

Would definitely recommend this course as an introduction or refresher to Data Science Math Skills!

:) Great Primer for Data Science Math!

A tremendously useful primer on the fundamentals of data science math.

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...... Learning this course I have gain many new and interesting skills.

Effective way to refresh and add the Data Science math skills!

Curso que aborda de forma breve mas muito eficiente o conteúdo proposto GOOD INTRODUCTION IN DATA SCIENCE MATHS The course is very basic and easy to understand with many example.

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basic math skills

It is a gentle introduction to basic math skills that everyone should have.

Probability part is good others are elementary math A good review of basic math skills, however I believed the "SUM RULE, CONDITIONAL PROBABILITY AND BAYES'THEOREM should be discussed much more in the last week module with more example and exercise.

Only advise I can give - change the name to "Basic Math Skills for Data science".

Gave a quick overview of the basic Math skills required for Data Science.

Very Effective Learning Perfect for beginners or as a review for those who have not used basic math skills for quite some time.

It helps you build the basic math skills in easy introducing way and you would enjoy it!

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easy to understand

It will refresh your memory and maybe it will also have an impact on your music : p This is a good learning course and nice to go through Easy to understand.

Very easy to understand explained clearly by the professors.

Very important Review course Very easy to understand and know how to succeed in the future on the learning path.

very good lecture and easy so very easy to understand the course Very nicely explained.

I would have appreciated some more in-depth explanation of the last week classes More practice problems would have made the course easier great sometime the lecture is too easy to understand and after some week it goes too hard to understand even it not a hard thing but sometime the lecturer make it so hard so it can make confuse.

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high school

Generally pretty good, a little slow and simple to start The first three weeks are pretty easy high school math.

A little bit easy if you have solid high school math background.

Really helpful in understanding terms in simple way Good to revise mathematical concepts I found it quite engaging and challenging at times to get my head back around high school maths!

Muy buen curso como base para el analisis de datos Highly recommended.. Easy and suitable for beginners with high school math skills.

Basic math course help to get revise all the high school concept.

Suitable for high school students.

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.

I am a high school sophomore and I loved this course.

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bayes theorem

It reviews the basics of sets, plotting, sigma notation, derivatives, logarithms, mean and variance, Bayes theorem, etc.

Although, more emphasis could have been placed on industrial examples but still the course is a great start for anyone The Bayes theorem and binomial theorem needs more examples.

Started off easy but got a little tricky in the end with Bayes Theorem.

This course helped me a lot in better understanding Bayes Theorem.

But I had to search around various other resources before I got the hang of Bayes theorem.

Also a tree diagram approach to both conditional and Bayes theorem will help get to the understanding faster.

Very well explained with real time examples Decent course to refresh the skills in probabilities for Data science cases A bit more information regarding Bayes theorem, Examples and how to tackle them would be better.

Great intro to bayes theorem.

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first two weeks

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.

Overall good refresh The first two weeks are good.

Great expérience for me.Thanks YouHerbaut Julien The first two weeks of the course were great!

Good Content and well Structured The second part was difficult for me because was short on examples and not as dynamic as the first two weeks.

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second half

The second half of Week 4 was good.

However, the second half of the class zips through concepts that need a lot more explanation than is provided.

The second half was not so great.

But overall I would say that was a nice beginning A pretty good course, though the second half wasn't explained as intuitively as the first half.

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will help

Adding few advance topics like various distributions will help too.

More focus on derivatives will help.

It will help the students understand your information better.

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Careers

An overview of related careers and their average salaries in the US. Bars indicate income percentile.

AD, Data Science $47k

Associate Data Science Supervisor $55k

Science writer / data analyst $63k

Genomic Data Science Programmer $75k

Volunteer Director of Data Science $78k

Expert Data Science Supervisor $79k

Supervisor 1 Data Science Supervisor $91k

Guest Director of Data Science $101k

Data Science Architect $105k

Head of Data Science $131k

Assistant Director 1 of Data Science $133k

Owner Director of Data Science $149k

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Rating 4.3★ based on 491 ratings
Length 5 weeks
Effort Four weeks, 3-5 hours per week.
Starts Jul 17 (40 weeks ago)
Cost $49
From Duke University, University of Geneva via Coursera
Instructors Daniel Egger, Paul Bendich, Tina Ambos, Gilbert Probst, Lea Stadtler, Bruce Jenks, Stephan Mergenthaler, Julian Fleet, Cassandra Quintanilla, Claudia Gonzalez Romo, Sebastian Buckup
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science Business Mathematics
Tags Data Science Data Analysis Business Math And Logic Leadership And Management

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