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Data Science Math Skills

Created by: Daniel Egger

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Overall Score : 88 / 100

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Course Description

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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Instructor Details

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Daniel Egger has more than seventeen years experience creating new software products and services, as founder and CEO of a series of venture-backed information technology companies, and as Managing Partner in a venture capital fund. Egger is Executive in Residence in Duke University's Master of Engineering Management Program and has taught courses in entrepreneurship and venture capital at Duke since 2003. He was formerly the Howard Johnson Foundation Entrepreneur-in-Residence in Duke's Markets and Management Program for undergraduates.

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Reviews

4.4

433 reviews in total

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By Hafiz P on 15-Nov-19

wonderfully designed course for refreshing my math skills

By Andrew F on 14-Nov-19

Great course! I really learned a lot.

By Katya K on 11-Nov-19

the first few lectures, first half is really easy to follow, quizzes are a great way of firming up the new knowledge. Last few lectures are very challenging comparing to the beginning of the course, and I felt that some have missed key steps unexplained. The final quiz doesn't provide feedback which makes it useless as a way to recapitulate and practice.

By Francine S on 9-Nov-19

Step by step course! Perfect for beginners. I highly recommend it.

By Chris on 8-Nov-19

You guys need to give better practice examples and scenarios in Weeks 3 and 4. That being said, I think the courses you presented give a nice foundation. I'm going to practice on my own time finding problems of the subjects you've spoken about.

By Abhishek R on 7-Nov-19

Every part covered gives a good introduction to the world of data science as intended. However in my personal opinion the part on probability was covered a bit hastily, though the quizzes will force you get some in-depth understanding

By Yan T on 1-Nov-19

Great course brushing off math skills with quiz in the end of each module. The last module is the most difficult, it'll be better if more examples be demonstrated. Good pace and a good course for those who need to get an idea of some topics.

By Michael B on 26-Oct-19

A veces las explicaciones no son tan claras

By Ahmed T on 25-Oct-19

Well-described concise notes and if you do not understand anything, the author provides written notes with every lecture.

By fulvio c on 24-Oct-19

It's a very intersting training in order to refresh your memory.

By Mahnaz K on 22-Oct-19

The course overall was great. So much math was covered that it is hard to believe it was all done in 4-5 weeks required to complete the course. It was well taught-- very relevant and clear for the most part. I have had all this math in the past so I had a frame of reference but without it I think it would be hard to follow. Having said that, I found the Probability lectures hard to follow. It seemed you need to know a lot of probability theory beforehand. Also the videos were too short in this sections and went very fast. The videos need to be 20-25 minutes with more examples. The quizzes in this section were the hardest because not many examples were given in the lecture. Overall though I feel accomplished and feel I can tackle the math that comes my way when I pursue my data science degree. Thank you for putting together a course with the background math needed for data science.

By Alieldin R on 14-Oct-19

The course was very good and well thought of, a great refresher for very important concepts, the instructors are very good at simplifying the material and making it very understandable.

Showing 12 of 433 reviews