Big Data Fundamentals

Description

In this course, you will learn:

• MapReduce knowledge and application.
• Understanding the frequency of event occurrences in huge data.
• In Big Data, how to develop algorithms for stream processing and counting frequent components.
• PageRank algorithms must be understood and designed.
• Recognize the random walk methods that underpin them.

Syllabus:

1. The basics of working with big data
2. Web and social networks
3. Clustering big data
4. Google web search
5. Parallel and distributed computing using MapReduce
6. Computing similar documents in big data
7. Products frequently bought together in stores
8. Movie and music recommendations
9. Google's AdWordsTM System
10. Mining rapidly arriving data streams