Math for Data Science Masterclass
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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:
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Understanding Data Concepts
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Measurements of Dispersion and Central Tendency
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Different ways to visualize data
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Permutations
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Combinatorics
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Bayes’ Theorem
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Random Variables
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Joint Distributions
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Covariance and Correlation
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Probability Mass and Density Functions
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Binomial, Bernoulli, and Poisson Distributions
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Normal Distribution and Z-Scores
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Sampling and Bias
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Central Limit Theorem
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Hypothesis Testing
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Linear Regression
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and much more!
Enroll today and we’ll see you inside the course!
Krista and Jose
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3Introduction to Core Data Concepts
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4Measurements of Central Tendency - Mean, Median, and Mode
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5Check-In Quiz: Central Tendency
Hi there!
Let's quickly check your knowledge with a quick question. If you watched the previous lecture, this question should be fairly easy to answer.
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6Measurements of Dispersion - Variance and Standard Deviation
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7Check-in Quiz: Measurements of Dispersion
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8Quartiles and IQR
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9Check-in Quiz: Quartiles and IQR
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10Introduction to Visualizing Data
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11Scatter Plots
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12Check-in Quiz: Scatter Plots
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13Line Plots
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14Distribution Plots - Histograms
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15Check-in Quiz: Histograms
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16Categorical Plots - Bar Plots
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17Categorical/Distribution Plots - Box and Whisker Plots
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18Check-in Quiz: Box Plots
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19Other Plot Types - Violin Plot, KDE Plot
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20Common Plot Pitfalls
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26Introduction to Probability
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27Probability, Law of Large Numbers, Experimental vs. Expected
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28The Addition Rule, Union and Intersection, Venn Diagrams
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29Conditional Probability, Independent and Dependent
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30Bayes' Theorem
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31Discrete Probability
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32Transforming Random Variables
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33Combinations of Random Variables
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34Probability Practice Problem Set and Answers
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39Introduction to Data Distributions
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40Probability Mass Functions
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41Discrete Uniform Distribution - Dice Roll
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42Probability Density Functions
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43Continuous Uniform Distribution - Voltage
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44Cumulative Distribution Functions
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45Binomial Distribution
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46Bernoulli Distribution
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47Poisson Distribution
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48Data Distributions Practice Problem Set and Answers