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العربية

categories: Business & Professional Skills

Data
Data Analysis
SDG 8: Decent Work and Economic Growth
SDG 9: Industry, Innovation and Infrastructure

Your Guide to Learn Data Analysis

By
Nermin Elgrawany
Duration: 6 h 34 m / 81 lessons

Level: General

Course Language: Arabic

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

1.

Introduction

2.

Section Introduction

3.

What is Data and Types of Data

4 Minutes
4.

Statistics and Probability for Data Analysis

1 Minutes
5.

What is Analysis and Types of Analysis

2 Minutes
6.

Statistics Description

1 Minutes
7.

Data Analysis Process

3 Minutes
8.

Measures of Center

6 Minutes
9.

Data Analyst Skills

1 Minutes
1.

Introduction

2.

What is Data and Types of Data

4 Minutes
3.

What is Analysis and Types of Analysis

2 Minutes
4.

Data Analysis Process

3 Minutes
5.

Data Analyst Skills

1 Minutes
1.

Section Introduction

2.

Statistics and Probability for Data Analysis

1 Minutes
3.

Statistics Description

1 Minutes
4.

Measures of Center

6 Minutes
5.

Measures of Spread

5 Minutes
6.

IQR

2 Minutes
7.

Shape of Distribution

3 Minutes
8.

Outliers

4 Minutes
9.

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
1.

Module Introduction

2.

Collecting Data

1 Minutes
3.

Cleaning 1

14 Minutes
4.

Cleaning 2

6 Minutes
5.

Cleaning 3

4 Minutes
6.

Cleaning 4

8 Minutes
7.

Cleaning 5

5 Minutes
8.

Cleaning 6

5 Minutes
9.

Cleaning 7

4 Minutes
10.

Solver

5 Minutes
11.

Descriptive Stats

4 Minutes
12.

Confidence Interval

1 Minutes
13.

Hypothesis Testing

3 Minutes
14.

LR

5 Minutes
15.

prob.1

5 Minutes
16.

Prob.2

5 Minutes
17.

Vis.1

9 Minutes
18.

Vis.2

10 Minutes
1.

Introduction to SQL

3 Minutes
2.

Datatype & Structure

2 Minutes
3.

Install SQL

2 Minutes
4.

Intro to PostgreSQL

5 Minutes
5.

Import File

5 Minutes
6.

First Commands

5 Minutes
7.

Where Statement

12 Minutes
8.

Aggregation

5 Minutes
9.

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
1.

Introduction

1 Minutes
2.

Introduction to Data Visualization

5 Minutes
3.

Install & Orientation

3 Minutes
4.

Home Page

4 Minutes
5.

Data Source Page

7 Minutes
6.

Work Sheet

7.

Bar Chart

8 Minutes
8.

Line Chart

5 Minutes
9.

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.

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