Data Analysis Concepts

Overview/Description
Target Audience
Prerequisites
Expected Duration
Lesson Objectives
Course Number
Expertise Level

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Overview/Description
There are many software and programming tools available to data scientists. Before applying those tools effectively, you must understand the underlying concepts. In this course, you'll explore the underlying data analysis concepts needed to employ the software and programming tools effectively

Target Audience
Individuals with some programming and math experience working toward implementing data science in their everyday work

Prerequisites
None

Expected Duration (hours)
1.7

Lesson Objectives

Data Analysis Concepts

start the course

perform basic math operations required by data scientists

perform basic vector math operations required by data scientists

perform basic matrix math operations required by data scientists

perform a matrix decomposition

identify different forms of data

describe probability in terms of events and sample space size

describe basic properties of outcomes

apply probability rules in calculation

identify common continuous probability distributions

identify common discrete probability distributions

apply bayes theorem and describe how it is used in email spam algorithms

apply random sampling to A/B tests

identify and describe various statistical measures

describe the difference between an unbiased and biased estimator

describe sampling distributions and recognize the central limit theorem

define confidence intervals and work with margins of error

carrying out hypothesis tests and working with p-values

apply the chi-square test for categorical values

identify the given data set descriptions by their types

Course Number:
df_dses_a07_it_enus

Expertise Level
Beginner