Big Data

How to Analyze Big Data

4.3(87)7h 7m50 lectures5 sections

What you'll learn

Understand big data sources
Understand big data characteristics
Learn data analysis using Hadoop
Apply machine learning techniques
Use Knime and Jupyter tools
Analyze data for insights

About this course

Learn how to handle big data in this comprehensive course that covers the fundamentals of data collection, analysis, and processing using modern tools and techniques like Hadoop and Knime. The course is designed to equip you with the skills needed to apply machine learning techniques to big data for effective analysis and decision-making.

Expected outcomes

Master big data collection and analysis using modern techniques.
Understand how to use Hadoop for distributed data management.
Apply machine learning techniques to analyze big data.
Master data exploration tools like Knime and Jupyter.
Develop practical projects based on big data analysis.

Course content

Big Data Sources

8 lectures

Introduction7:04
Applications that Add Value to Data13:25
Big Data Sources2:42
Machines as Data Sources7:01
People as Data Sources5:46
Working with Unstructured Data5:38
Organizations as Data Sources7:08
Data Integration4:46

Characteristics of Big Data

7 lectures

Introduction to Big Data Characteristics2:59
Volume5:20
Variety5:14
Velocity5:42
Veracity7:52
Equity4:34
Value7:15

Data Analysis Steps

4 lectures

Data Science10:19
Building a Big Data Strategy7:55
The Five Components of Data Science5:43
Data Processing Steps8:33

Working with Hadoop

12 lectures

Distributed Operating System10:26
Distributed Computing Process8:02
Big Data Programming Models7:36
Why Hadoop?4:33
Explaining the Hadoop System13:39
Distributed File System in Hadoop7:42
Resource Management7:29
Simplest MapReduce Programming Model10:56
Computational Computing9:28
Installing Cloudera10:35
Working with Distributed File System in Cloudera11:33
Practical Application16:07

Machine Learning and Big Data

19 lectures

A Quick Look at Machine Learning11:43
Machine Learning and Big Data14:02
Operations Implemented Using Machine Learning8:41
Data Extraction9:26
Overview of Programs and Tools9:29
Installing Knime13:22
Working with Jupyter9:34
Features and Data8:24
Data Exploration5:38
Descriptive Statistics11:53
Data Validation8:30
Exploratory Visualizations13:56
Using Visualization with Knime8:59
Data Preparation5:04
Data Quality4:40
Data Quality Processing Techniques6:51
Feature Identification10:05
Feature Transformation7:03
Practical Application on Missing Data17:01

Instructor

Eng. Amr Abdel Fattah

Computer systems engineer specializing in mobile app and website development, with experience in creating popular platforms and web applications.

3,186 students20 courses

This course is part of the diploma

4.7(54)|5
Diploma in AI Application Development
5 courses
$79.99
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