Big Data
How to Analyze Big Data
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
1Big 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
2Characteristics of Big Data
7 lectures
- Introduction to Big Data Characteristics2:59
- Volume5:20
- Variety5:14
- Velocity5:42
- Veracity7:52
- Equity4:34
- Value7:15
3Data Analysis Steps
4 lectures
- Data Science10:19
- Building a Big Data Strategy7:55
- The Five Components of Data Science5:43
- Data Processing Steps8:33
4Working 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
5Machine 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
6,563 students20 courses
This course is part of the diploma
