# 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!

## &

Rating | 4.3★ based on 280 ratings |
---|---|

Length | 5 weeks |

Effort | Four weeks, 3-5 hours per week. |

Starts | Dec 10 (2 days 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 |

Free | Limited Content |

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

We analyzed reviews for this course to surface learners' thoughts about it

**math skills**
in 19 reviews

great course to refresh your math skills in data science projects improve week 4 videos Este curso lo recomiendo mucho a quienes estén interesados en refrescar sus conocimientos de matemáticas para pasar a cursos de estadística o data science.

This course is designed for those either without a college level math background (calculus, probability, etc) and thus need an introduction to fundamental math skills or for those who need a refresher.

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

Especially is possible understand everything by video companion which explain math skills in practice exercises.

For those with stronger math skills than me, it's probably a fairly easy course.

I wanted to review the concepts presented in this course to get back on track with my math skills.

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.

Suited for anyone with 12th grade math skills.

**high school**
in 8 reviews

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.

cannot believe I took a programming course without doing this - the math was taking me so long and it was because I hadn't finished high school math a decade ago (our school didn't require it) - really thankful to have found this course!

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.

**last week**
in 8 reviews

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.

The last week is very informative and helpful.

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.

**data science math**
in 6 reviews

A great fast introduction into Data Science Math Skills.

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

I am studying at the Data Science Math Skills to fill some math gaps, and also doing the Data Scientist Toolbox .

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.

**practice quizzes**
in 4 reviews

Thank you for the detailed guidance in the practice quizzes on incorrect answers as well!

The readings should also explain very weel what I'm doing and why I'm doing each step, and in the end explain the exercise as a whole.The practice quizzes should bring very real life examples (as thouse of VBS tests) and they have to match de guide text.The videos should be made only from the most comum doubts and mistakes in the practice quizzes.

Video companions and practice quizzes complement the lectures in an effective way and prepare the student well for the graded quizzes.

The explanations on the practice quizzes also fail in many cases to thoroughly explain why an answer is correct.

**two weeks**
in 3 reviews

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.

It is also explained why and how a presented concept is related to data science.The last two weeks however are to shallow and abstract in the explanations.

This wasn't the case in the first two weeks.

Blows right through a lot of fundamental concepts without a deep enough explanation or enough practice material (especially in the last two weeks).

## Careers

An overview of related careers and their average salaries in the US. Bars indicate income percentile (33rd - 99th).

Data Science/Analytics $66k

Data Science Supervisor $88k

Acting Data Science Supervisor $94k

Staff Data Science Supervisor $96k

Guest Data Science Manager $98k

Data Science Manager $108k

Vice President 3 of Data Science $143k

Acting Director of Data Science $143k

Director 2 of Data Science $157k

Director of Data Science $162k

Director 1 of Data Science $162k

Vice President 2 of Data Science $168k

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## &

Rating | 4.3★ based on 280 ratings |
---|---|

Length | 5 weeks |

Effort | Four weeks, 3-5 hours per week. |

Starts | Dec 10 (2 days 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 |

Free | Limited Content |

Language | English |

Subjects | Data Science Business Mathematics |

Tags | Data Science Data Analysis Business Math And Logic Leadership And Management |

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