Web Intelligence and Big Data

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Description

When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

This course is being simulateously offered at the Indian Institute of Technology Delhi as well as the Indraprastha Institute of Information Technology Delhi. This course is about building `web-intelligence' applications exploiting big data sources arising social media, mobile devices and sensors, using new big-data platforms based on the 'map-reduce' parallel programming paradigm.

About the Course

The past decade has witnessed the successful of application of many AI techniques used at `web-scale’, on what are popularly referred to as big data platforms based on the map-reduce parallel computing paradigm and associated technologies such as distributed file systems, no-SQL databases and stre…

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Frequently asked questions

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Didn't find what you were looking for? See also: Data Mining, Databases, SQL, Social Media, and Programming.

When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

This course is being simulateously offered at the Indian Institute of Technology Delhi as well as the Indraprastha Institute of Information Technology Delhi. This course is about building `web-intelligence' applications exploiting big data sources arising social media, mobile devices and sensors, using new big-data platforms based on the 'map-reduce' parallel programming paradigm.

About the Course

The past decade has witnessed the successful of application of many AI techniques used at `web-scale’, on what are popularly referred to as big data platforms based on the map-reduce parallel computing paradigm and associated technologies such as distributed file systems, no-SQL databases and stream computing engines. Online advertising, machine translation, natural language understanding, sentiment mining, personalized medicine, and national security are some examples of such AI-based web-intelligence applications that are already in the public eye. Others, though less apparent, impact the operations of large enterprises from sales and marketing to manufacturing and supply chains. In this course we explore some such applications, the AI/statistical techniques that make them possible, along with parallel implementations using map-reduce and related platforms.

About the Instructor(s)

Dr. Gautam Shroff is Vice President & Chief Scientist, Tata Consultancy Services and heads TCS’ Innovation Lab in Delhi, India, and is teaching this course as in an adjunct capacity at IIT Delhi and IIIT Delhi.
Prior to joining TCS in 1998, Dr. Shroff had been on the faculty of the California Institute of Technology, Pasadena, USA and thereafter of the Department of Computer Science and Engineering at Indian Institute of Technology, Delhi, India. He has also held visiting positions at NASA Ames Research Center in Mountain View, CA, and at Argonne National Labs in Chicago. In 1994 he was conferred the "Young Scientist Award" from the Department of Atomic Energy (Govt. of India).

Dr. Shroff has published over 30 research papers in the areas of computational mathematics, parallel computing, distributed systems, software architecture, software engineering, and information fusion. He has also written a book “Enterprise Cloud Computing” published by Cambridge University Press in 2010. Dr. Shroff graduated from the Indian Institute of Technology, Kanpur, India, in 1985 and received his Ph.D. in Computer Science from Rensselaer Polytechnic Institute, NY, USA, in 1990.

Course Syllabus

Introduction and Overview Look: Search, Indexing and Memory Listen: Streams, Information and Language, Analyzing Sentiment and Intent Load: Databases and their evolution, Big data; technology and dimensionality Learn: Classification, Clustering, and Mining, Information Extraction Connect: Reasoning: Logic and its Limits, Dealing with Uncertainty Predict: Prediction: What is ‘interesting’, and why? Predictive Analytics in Business, Applications in National Security Applications in Online Advertising

Recommended Background

Basic programming, SQL and data structures Exposure to probability, statistics and matrices

Course Format

The class will consist of lecture videos, which are between 5 and 8 minutes in length. There will be 1-2 integrated quiz questions per video. There will also be standalone homeworks that are not part of video lectures, two programming assignments, and a final exam.

FAQ

  • Will I get a certificate after completing this class?

    Students registered for the course at IIT- Delhi or IIIT-Delhi will get credit as part of the normal curriculum. Other students will not get any certification from either institution. However, all students who complete the course with distinction can request the instructor for a personal reference by email.

  • Do I need any additional materials?

    Access to a computer on which Python 2.7 either is already installed or can be downloaded and installed.

Provided by:

University: Indian Institute of Technology Delhi, Indraprastha Institute of Information Technology Delhi

Instructor(s): Gautam Shroff

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There are no frequently asked questions yet. Send an Email to info@springest.com