Your Guide to Learn Data Analysis

categories: Technology, Science & Productivity

Data

Data Analysis

SDG 8: Decent Work and Economic Growth

SDG 9: Industry, Innovation and Infrastructure

By the end of this course, you will be able to

The definition of statistics and probabilities and their types, together with learning how to analyze data using Microsoft Excel and create effective dashboards.
The difference between data, information, and knowledge, together with understanding the concept of data analysis and the skills that every data analyst should possess.
How to exploit Tableau and PostgreSQL to analyze, evaluate, and visualize data, starting from how to download them and all the way to making data-driven decisions.

Course details

6 h 34 m/81 lessons
Last updated: 10/10/2022
1 learning resources
Course completion certificate

Course Content

Free lessons

Introduction

Section Introduction

What is Data and Types of Data

4 Minutes

Statistics and Probability for Data Analysis

1 Minutes

What is Analysis and Types of Analysis

2 Minutes

Statistics Description

1 Minutes

Data Analysis Process

3 Minutes

Measures of Center

6 Minutes

Data Analyst Skills

1 Minutes

1. Introduction To Data Analysis

Introduction

What is Data and Types of Data

4 Minutes

What is Analysis and Types of Analysis

2 Minutes

Data Analysis Process

3 Minutes

Data Analyst Skills

1 Minutes

2. Statistics and Probability For Data Analysis

Section Introduction

Statistics and Probability for Data Analysis

1 Minutes

Statistics Description

1 Minutes

Measures of Center

6 Minutes

Measures of Spread

5 Minutes

IQR

2 Minutes

Shape of Distribution

3 Minutes

Outliers

4 Minutes

Visualize Data

2 Minutes

10.

Notation

6 Minutes

11.

Intro Inferential Stats

4 Minutes

12.

Estimation

1 Minutes

13.

Confidence Interval 1

4 Minutes

14.

z-test vs. t-test

3 Minutes

15.

CI Examples

5 Minutes

16.

Hypothesis Testing

3 Minutes

17.

Types of Tests

3 Minutes

18.

HT Example 1

7 Minutes

19.

HT Example 2

4 Minutes

20.

Regression

4 Minutes

21.

Cor.Coeff. vs. R2

2 Minutes

22.

LR Examples

7 Minutes

23.

MLR Examples

6 Minutes

24.

Stat.Sig vs Prac.Sig

1 Minutes

25.

Probability

3 Minutes

26.

Probability Basics Example

3 Minutes

27.

Binomial Distribution

2 Minutes

28.

Conditional Probability

2 Minutes

3. Excel For Data Analysis

Section Introduction

Collecting Data

1 Minutes

Cleaning 1

14 Minutes

Cleaning 2

6 Minutes

Cleaning 3

4 Minutes

Cleaning 4

8 Minutes

Cleaning 5

5 Minutes

Cleaning 6

5 Minutes

Cleaning 7

4 Minutes

10.

Solver

5 Minutes

11.

Descriptive Stats

4 Minutes

12.

Confidence Interval

1 Minutes

13.

Hypothesis Testing

3 Minutes

14.

5 Minutes

15.

prob.1

5 Minutes

16.

Prob.2

5 Minutes

17.

Vis.1

9 Minutes

18.

Vis.2

10 Minutes

4. SQL For Data Analysis

Introduction to SQL

3 Minutes

Datatype & Structure

2 Minutes

Install SQL

2 Minutes

Intro to PostgreSQL

5 Minutes

Import File

5 Minutes

First Commands

5 Minutes

Where Statement

12 Minutes

Aggregation

5 Minutes

Joins

9 Minutes

10.

Having & Groupby

5 Minutes

11.

Case Statement

4 Minutes

12.

Subqueries

5 Minutes

13.

Mechanism

14.

Text Functions

11 Minutes

15.

Date Functions

5 Minutes

16.

db Operators

12 Minutes

17.

Cleaning Data (Duplicated)

13 Minutes

18.

Cleaning Data (Null)

7 Minutes

19.

Cleaning Data (Datatype)

4 Minutes

5. Tableau

Introduction

1 Minutes

Introduction to Data Visualization

5 Minutes

Install & Orientation

3 Minutes

Home Page

4 Minutes

Data Source Page

7 Minutes

Work Sheet

Bar Chart

8 Minutes

Line Chart

5 Minutes

Pie Chart

5 Minutes

10.

Dashboard

4 Minutes

11.

Story

3 Minutes

learning resources

About this course

Having chunks of data is one thing, and using that data to empower strategic business decisions is a whole another story. Simply because, if you don’t know how to exploit the asset you have at hand, you will never be able to hold your ground in today’s data-driven fast-paced world. Therefore, if you are a beginner who is keen to explore the data analysis field, starting from the definition of data and all the way to the programming languages that can bring your data to life, this comprehensive two-part series is what you’re looking for.

Course requirements and prerequisites

There are no requirements for this course. Your interest in the topic and your commitment to learning are all you need to achieve the utmost benefit from this course.