Mô tả

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.  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

  • Random 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

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Yêu cầu

Nội dung khoá học

11 sections

Introduction

2 lectures
Welcome to the Course! Important Info in this Lecture!
00:42
Course Overview and Curriculum
04:10

Core Data Concepts

7 lectures
Introduction to Core Data Concepts
16:03
Measurements of Central Tendency - Mean, Median, and Mode
26:33
Check-In Quiz: Central Tendency
1 question
Measurements of Dispersion - Variance and Standard Deviation
20:33
Check-in Quiz: Measurements of Dispersion
1 question
Quartiles and IQR
18:28
Check-in Quiz: Quartiles and IQR
1 question

Visualizing Data

11 lectures
Introduction to Visualizing Data
20:38
Scatter Plots
21:35
Check-in Quiz: Scatter Plots
1 question
Line Plots
10:19
Distribution Plots - Histograms
13:21
Check-in Quiz: Histograms
1 question
Categorical Plots - Bar Plots
08:06
Categorical/Distribution Plots - Box and Whisker Plots
08:00
Check-in Quiz: Box Plots
1 question
Other Plot Types - Violin Plot, KDE Plot
12:49
Common Plot Pitfalls
11:55

Combinatorics

5 lectures
Introduction to Combinatorics
12:19
Factorials
16:24
Permutations
10:50
Combinations
14:47
Combinatorics Practice Problem Set and Answers
00:03

Probability

9 lectures
Introduction to Probability
23:01
Probability, Law of Large Numbers, Experimental vs. Expected
21:05
The Addition Rule, Union and Intersection, Venn Diagrams
18:10
Conditional Probability, Independent and Dependent
15:50
Bayes' Theorem
13:15
Discrete Probability
26:02
Transforming Random Variables
26:06
Combinations of Random Variables
16:18
Probability Practice Problem Set and Answers
00:04

Joint Distributions

4 lectures
Introduction to Joint Distributions
20:54
Covariance
19:15
Pearson Correlation Coefficient
15:48
Joint Distribution Practice Problem Set and Answers
00:03

Data Distributions

10 lectures
Introduction to Data Distributions
15:56
Probability Mass Functions
14:14
Discrete Uniform Distribution - Dice Roll
06:45
Probability Density Functions
18:51
Continuous Uniform Distribution - Voltage
11:11
Cumulative Distribution Functions
12:48
Binomial Distribution
21:30
Bernoulli Distribution
13:47
Poisson Distribution
13:41
Data Distributions Practice Problem Set and Answers
00:03

The Normal Distribution

6 lectures
Introduction to The Normal Distribution
15:58
Mean, Variance, and Standard Deviation
16:00
Normal Distribution
15:29
Standard Normal Distribution
08:00
Z-Scores
19:49
Normal Distribution Practice Problem Set and Answers
00:03

Sampling

6 lectures
Introduction to Sampling
14:29
Sampling and Bias
27:16
The Central Limit Theorem
21:33
The Student's t-Distribution
11:01
Confidence Interval for the Mean
20:31
Sampling Practice Problem Set and Answers
00:03

Hypothesis Testing

7 lectures
Introduction to Hypothesis Testing
16:17
Inferential Statistics and Hypotheses
11:04
Significance Level and Type I and II Errors
17:14
Test Statistics for One- and Two-Tailed Tests
14:28
The p-Value and Rejecting the Null
21:49
A|B Testing
21:01
Hypothesis Testing Practice Problem Set and Answers
00:03

Regression

7 lectures
Introduction to Regression
12:58
Scatterplots and Regression
08:17
Correlation Coefficient and the Residual
22:45
Coefficient of Determination and the RMSE
17:08
Chi-Square Tests
16:53
ANOVA
24:49
Regression Practice Problem Set and Answers
00:03

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