Math for Data Science Masterclass

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Jose Portilla,Krista King

16:06:06

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1. Introduction

1. Welcome to the Course! Important Info in this Lecture!.html

2. Course Overview and Curriculum.mp4

04:10

2. Core Data Concepts

1. Introduction to Core Data Concepts.mp4

16:03

2. Measurements of Central Tendency - Mean, Median, and Mode.mp4

26:33

3. Measurements of Dispersion - Variance and Standard Deviation.mp4

20:33

4. Quartiles and IQR.mp4

18:28

3. Visualizing Data

1. Introduction to Visualizing Data.mp4

20:38

2. Scatter Plots.mp4

21:35

3. Line Plots.mp4

10:19

4. Distribution Plots - Histograms.mp4

13:21

5. Categorical Plots - Bar Plots.mp4

08:06

6. CategoricalDistribution Plots - Box and Whisker Plots.mp4

08:00

7. Other Plot Types - Violin Plot, KDE Plot.mp4

12:49

8. Common Plot Pitfalls.mp4

11:55

4. Combinatorics

1. Introduction to Combinatorics.mp4

12:19

2. Factorials.mp4

16:24

3. Permutations.mp4

10:50

4. Combinations.mp4

14:47

5.1 03-Combinatorics-Practice-Questions_Answers.pdf

5.2 03-Combinatorics-Practice-Questions.pdf

5. Combinatorics Problem Set.html

5. Probability

1. Introduction to Probability.mp4

23:01

2. Probability, Law of Large Numbers, Experimental vs. Expected.mp4

21:05

3. The Addition Rule, Union and Intersection, Venn Diagrams.mp4

18:10

4. Conditional Probability, Independent and Dependent.mp4

15:50

5. Bayes Theorem.mp4

13:15

6. Discrete Probability.mp4

26:02

7. Transforming Random Variables.mp4

26:06

8. Combinations of Random Variables.mp4

16:18

9.1 04-Probability-Practice-Questions_Answers.pdf

9.2 04-Probability-Practice-Questions.pdf

9. Probability Practice Problem Set and Answers PDFs.html

6. Joint Distributions

1. Introduction to Joint Distributions.mp4

20:54

2. Covariance.mp4

19:15

3. Pearson Correlation Coefficient.mp4

15:48

4.1 05-Joint Distributions-Practice-Questions_Answers.pdf

4.2 05-Joint Distributions-Practice-Questions.pdf

4. Joint Distribution Practice Problem Set and Answers.html

7. Data Distributions

1. Introduction to Data Distributions.mp4

15:56

2. Probability Mass Functions.mp4

14:14

3. Discrete Uniform Distribution - Dice Roll.mp4

06:45

4. Probability Density Functions.mp4

18:51

5. Continuous Uniform Distribution - Voltage.mp4

11:11

6. Cumulative Distribution Functions.mp4

12:48

7. Binomial Distribution.mp4

21:30

8. Bernoulli Distribution.mp4

13:47

9. Poisson Distribution.mp4

13:41

10.1 06-Data- Distributions-Practice-Questions_Answers.pdf

10.2 06-Data- Distributions-Practice-Questions.pdf

10. Data Distributions Practice Problem Set and Answers.html

8. The Normal Distribution

1. Introduction to The Normal Distribution.mp4

15:58

2. Mean, Variance, and Standard Deviation.mp4

16:00

3. Normal Distribution.mp4

15:29

4. Standard Normal Distribution.mp4

08:00

5. Z-Scores.mp4

19:49

6.1 07-The Normal Distribution-Practice-Questions_Answers.pdf

6.2 07-The Normal Distribution-Practice-Questions.pdf

6. Normal Distribution Practice Set and Answers.html

9. Sampling

1. Introduction to Sampling.mp4

14:29

2. Sampling and Bias.mp4

27:16

3. The Central Limit Theorem.mp4

21:33

4. The Students t-Distribution.mp4

11:01

5. Confidence Interval for the Mean.mp4

20:31

6.1 08-Sampling-Practice-Questions_Answers.pdf

6.2 08-Sampling-Practice-Questions.pdf

6. Sampling Practice Problem Set and Answers.html

10. Hypothesis Testing

1. Introduction to Hypothesis Testing.mp4

16:17

2. Inferential Statistics and Hypotheses.mp4

11:04

3. Significance Level and Type I and II Errors.mp4

17:14

4. Test Statistics for One- and Two-Tailed Tests.mp4

14:28

5. The p-Value and Rejecting the Null.mp4

21:49

6. AB Testing.mp4

21:01

7.1 09-Hypothesis_Testing-Practice-Questions_Answers.pdf

7.2 09-Hypothesis_Testing-Practice-Questions.pdf

7. Hypothesis Testing Practice Problem Set and Answers.html

11. Regression

1. Introduction to Regression.mp4

12:58

2. Scatterplots and Regression.mp4

08:17

3. Correlation Coefficient and the Residual.mp4

22:45

4. Coefficient of Determination and the RMSE.mp4

17:08

5. Chi-Square Tests.mp4

16:53

6. ANOVA.mp4

24:49

7.1 10-Regression-Practice-Questions_Answers.pdf

7.2 10-Regression-Practice-Questions.pdf

7. Regression Practice Problem Set and Answers.html

Description

Learn about probability, statistics, and more using the mathematics that are foundational to the field of data science.

What You'll Learn?

Understand core concepts about data quality and quantity
Learn about how to measure data with statistics
Discover how to visualize data with a variety of plot types
Use combinatorics to calculate permutations and combinations of objects
Understand the key ideas in using probability to solve problems
Learn how to use data distributions with real world data
Discover the powerful insights from the normal distribution
Use sampling and the central limit theorem
Understand hypothesis testing on sample groups
Cover the basics of linear regression

Who is this for?

Anyone interested in learning more about the mathematics behind data science

More details

Description
Welcome to the best online course for learning about the Math behind the field of Data Science!
Working together for the first time ever, Krista King and Jose Portilla have combined forces to deliver you a best in class course experience in how to use mathematics to solve real world data science problems. This course has been specifically designed to help you understand the mathematical concepts behind the field of data science, so you can have a first principles level understanding of how to use data effectively in an organization.
Often students entering the field of data science are confused on where to start to learn about the fundamental math behind the concepts. This course was specifically designed to help bridge that gap and provide students a clear, guided path through the complex and interesting world of math used in the field of data science. Designed to balance theory and application, this is the ultimate learning experience for anyone wanting to really understand data science.
Why choose this course?
Combined together, Krista and Jose have taught over 3.2 million students about data science and mathematics and their joint expertise means you'll be able to get the best and clearest mathematical explanations from Krista with framing about real world data science applications from Jose.Â At the end of each section is a set of practice problems developed from real-world company situations, where you can directly apply what you know to test your understanding.
What's covered in this course?
In this course, we'll cover:
Understanding Data Concepts
Measurements of Dispersion and Central Tendency
Different ways to visualize data
Permutations
Combinatorics
Bayes' Theorem
RandomÂ Variables
Joint Distributions
Covariance and Correlation
Probability Mass and Density Functions
Binomial, Bernoulli, and Poisson Distributions
Normal Distribution and Z-Scores
Sampling and Bias
Central Limit Theorem
Hypothesis Testing
Linear Regression
and much more!
Enroll today and we'll see you inside the course!
Krista and Jose
Who this course is for:
Anyone interested in learning more about the mathematics behind data science

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Jose Marcial Portilla has a BS and MS in Mechanical Engineering from Santa Clara University and years of experience as a professional instructor and trainer for Data Science, Machine Learning and Python Programming. He has publications and patents in various fields such as microfluidics, materials science, and data science. Over the course of his career he has developed a skill set in analyzing data and he hopes to use his experience in teaching and data science to help other people learn the power of programming, the ability to analyze data, and the skills needed to present the data in clear and beautiful visualizations. Currently he works as the Head of Data Science for Pierian Training and provides in-person data science and python programming training courses to employees working at top companies, including General Electric, Cigna, The New York Times, Credit Suisse, McKinsey and many more. Feel free to check out the website link to find out more information about training offerings.

Krista King

Instructor's Courses

Math class was always so frustrating.I’d go to a class, spend hours on homework, and three days later have an “Ah-ha!” moment about how the problems worked that could have slashed my homework time in half.I’d think, “WHY didn’t my teacher just tell me this in the first place?!”So I started tutoring to keep others out of that aggravating, time-sucking cycle. Since then, I’ve recorded tons of videos and written out cheat-sheet style notes and formula sheets to help every math student—from basic middle school classes to advanced college calculus—figure out what’s going on, understand the important concepts, and pass their classes, once and for all.

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