# Big Data Computing

- Institution: IIT Patna
- Department: Computer Science and Engineering
- Teacher: Prof. Rajiv Misra
- Level: Graduate
- Language: English
- Subjects: Computer science, Engineering
- Source: [NPTEL](https://nptel.ac.in/courses/106104189)
- Licence: [CC BY-NC-SA](https://nptel.ac.in/faq) (Non-commercial use only.)
- Syllabus: [at the source](https://nptel.ac.in/courses/106104189)
- Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

In today's fast-paced digital world , the incredible amount of data being generated every minute has grown tremendously from sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and GPS signals from cell phone to name a few. This amount of large data with different velocities and varieties is termed as big data and its analytics enables professionals to convert extensive data through statistical and quantitative analysis into powerful insights that can drive efficient decisions. This course provides an in-depth understanding of terminologies and the core concepts behind big data problems, applications, systems and the techniques, that underlie today's big data computing technologies. It provides an introduction to some of the most common frameworks such as Apache Spark, Hadoop, MapReduce, Large scale data storage technologies such as in-memory key/value storage systems, NoSQL distributed databases, Apache Cassandra, HBase and Big Data Streaming Platforms such as Apache Spark Streaming, Apache Kafka Streams that has made big data analysis easier and more accessible. And while discussing the concepts and techniques, we will also look at various applications of Big Data Analytics using Machine Learning, Deep Learning, Graph Processing and many others. The course is suitable for all UG/PG students and practicing engineers/ scientists from the diverse fields and interested in learning about the novel cutting edge techniques and applications of Big Data Computing.

PREREQUISITES : Data Structure & Algorithms, Computer Architecture, Operating System, Database Management Systems

INDUSTRY SUPPORT : Companies like Amazon, Microsoft, Google, IBM, Facebook

## Lectures

1. [Introduction to Big Data](https://invisiblenetwork.ai/learn/nptel/106104189/ca7a0fa2fd36) (YouTube)
2. [Big Data Enabling Technologies](https://invisiblenetwork.ai/learn/nptel/106104189/8496f5eb7489) (YouTube)
3. [Hadoop Stack for Big Data](https://invisiblenetwork.ai/learn/nptel/106104189/e8f6b0592457) (YouTube)
4. [Hadoop Distributed File System (HDFS)](https://invisiblenetwork.ai/learn/nptel/106104189/a06e009e4a3a) (YouTube)
5. [Hadoop MapReduce 1.0](https://invisiblenetwork.ai/learn/nptel/106104189/a8c418c088c0) (YouTube)
6. [Hadoop MapReduce 2.0 (Part-I)](https://invisiblenetwork.ai/learn/nptel/106104189/fced365758c2) (YouTube)
7. [Hadoop MapReduce 2.0 (Part-II)](https://invisiblenetwork.ai/learn/nptel/106104189/5352f2314f8b) (YouTube)
8. [MapReduce Examples](https://invisiblenetwork.ai/learn/nptel/106104189/295bb6fe40ae) (YouTube)
9. [Parallel Programming with Spark](https://invisiblenetwork.ai/learn/nptel/106104189/77e8fa3d3116) (YouTube)
10. [Introduction to Spark](https://invisiblenetwork.ai/learn/nptel/106104189/81cd96d1bc7c) (YouTube)
11. [Spark Built-in Libraries](https://invisiblenetwork.ai/learn/nptel/106104189/8b220ec72c9a) (YouTube)
12. [Design of Key-Value Stores](https://invisiblenetwork.ai/learn/nptel/106104189/48f73d27a3f4) (YouTube)
13. [Data Placement Strategies](https://invisiblenetwork.ai/learn/nptel/106104189/b85e14066875) (YouTube)
14. [CAP Theorem](https://invisiblenetwork.ai/learn/nptel/106104189/9dcddf6dc5dc) (YouTube)
15. [Consistency Solutions](https://invisiblenetwork.ai/learn/nptel/106104189/15cae7b14c60) (YouTube)
16. [CQL (Cassandra Query Language)](https://invisiblenetwork.ai/learn/nptel/106104189/4f8900686db9) (YouTube)
17. [Design of Zookeeper](https://invisiblenetwork.ai/learn/nptel/106104189/dbfc3f60db1b) (YouTube)
18. [Design of HBase](https://invisiblenetwork.ai/learn/nptel/106104189/2cfa7287fe13) (YouTube)
19. [Spark Streaming and Sliding Window Analytics (Part-I)](https://invisiblenetwork.ai/learn/nptel/106104189/3829af9e148a) (YouTube)
20. [Spark Streaming and Sliding Window Analytics (Part-II)](https://invisiblenetwork.ai/learn/nptel/106104189/c8a79fdd089c) (YouTube)
21. [Sliding Window Analytics](https://invisiblenetwork.ai/learn/nptel/106104189/823e8a113c84) (YouTube)
22. [Introduction to Kafka](https://invisiblenetwork.ai/learn/nptel/106104189/5da47fd97069) (YouTube)
23. [Big Data Machine Learning (Part-I)](https://invisiblenetwork.ai/learn/nptel/106104189/88ffe7207320) (YouTube)
24. [Big Data Machine Learning (Part-II)](https://invisiblenetwork.ai/learn/nptel/106104189/9c8e8b401f4c) (YouTube)
25. [Machine Learning Algorithm K-means using Map Reduce for Big Data Analytics](https://invisiblenetwork.ai/learn/nptel/106104189/785426314dfd) (YouTube)
26. [Parallel K-means using Map Reduce on Big Data Cluster Analysis](https://invisiblenetwork.ai/learn/nptel/106104189/ee5e26b5e9ba) (YouTube)
27. [Decision Trees for Big Data Analytics](https://invisiblenetwork.ai/learn/nptel/106104189/aac823e76118) (YouTube)
28. [Big Data Predictive Analytics (Part-I)](https://invisiblenetwork.ai/learn/nptel/106104189/1453059265f2) (YouTube)
29. [Big Data Predictive Analytics (Part-II)](https://invisiblenetwork.ai/learn/nptel/106104189/31f1abb551ec) (YouTube)
30. [Parameter Servers](https://invisiblenetwork.ai/learn/nptel/106104189/a66f1135a239) (YouTube)
31. [PageRank Algorithm in Big Data](https://invisiblenetwork.ai/learn/nptel/106104189/b1e7fa227798) (YouTube)
32. [Spark GraphX & Graph Analytics (Part-I)](https://invisiblenetwork.ai/learn/nptel/106104189/1d17acc6fc00) (YouTube)
33. [Spark GraphX & Graph Analytics (Part-II)](https://invisiblenetwork.ai/learn/nptel/106104189/7ff9b09229d0) (YouTube)
34. [Case Study: Flight Data Analysis using Spark GraphX](https://invisiblenetwork.ai/learn/nptel/106104189/c128937a115e) (YouTube)