Aegis School of Business, Data Science, Cyber Security & Telecommunication
| Application fee: | 1000 * INR |
| Course fee: | 25000 * INR |
| GST: | 18 % |
Hadoop: Big Data Processing and Management
Details
| Certification Body: | Aegis School of Data Science |
|---|---|
| Location: | On-campus (India, Mumbai, Pune, Bangalore) |
| Type: | Certificate course |
| Director: | Dr. Vinay Kulkarni |
| Coordinator: | Ritin Joshi |
| Language: | English |
| Course fee: | 25000 * INR |
| GST: | 18% |
| Total course fee: | 29500 * INR |
| Rating: |
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Course Details
Introduction:
The explosive growth of digital data has created unprecedented opportunities for businesses and organizations to gain valuable insights from it. But traditional data processing techniques and tools are insufficient to handle the volume, velocity, and variety of big data. Hadoop is a powerful, open-source big data processing and management framework that enables organizations to store, process, and analyze large volumes of data in a distributed and scalable manner.
Why Hadoop:
As a data scientist, having knowledge of Hadoop is essential as it enables you to work with massive amounts of data, and gain valuable insights from it. Hadoop has become an industry standard for big data processing, and it's important to understand its concepts, architecture, and tools to stay ahead of the competition.
Learning Outcome:
The Hadoop: Big Data Processing and Management course will provide you with a deep understanding of Hadoop's concepts, architecture, and tools. You will learn how to develop MapReduce applications, architect Hadoop-based applications, and operate Hadoop clusters. By the end of the course, you will have the skills and knowledge necessary to process and manage big data using Hadoop.
Hadoop Course Overview
Through lectures, hands-on exercises, case studies, and projects the students will explore the Hadoop ecosystem, learning topics such as:
- What is Hadoop and the real-world problems it solves
- Understand MapReduce concepts and how it works
- Write MapReduce programs
- Architect Hadoop-based applications
- Understand Hadoop operations
Prerequisites and Requirements
- Programming proficiency in Java or Python is required.
Note: For students who do not have programming background in Java or Python, additional readings or learning videos will be prescribed. The programming prerequisites will need to be completed within the first 2 weeks of the course.
Course Contents
- Introduction to Hadoop: Real-World Hadoop Applications and Use Cases, Hadoop Ecosystem & projects, Types of Hadoop Processing, Hadoop Distributions, Hadoop Installation.
- Hadoop MapReduce: Developing a MapReduce Application, MapReduce Internals, MapReduce I/O, Examples illustrating MapReduce Features.
- Hadoop Application Architectures: Data Modeling, Data Ingestion, and Data Processing in Hadoop.
- Hadoop Projects: Practical Tips for Hadoop Projects.
- Hadoop Operations: Planning a Hadoop Cluster, Installation and Configuration, Security, and Monitoring.
- Hadoop Case Studies: A series of Group Discussions and Student Project Presentations.