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Online Course

Web Intelligence and Big Data

Indian Institute of Technology Delhi and Indraprastha Institute of Information Technology Delhi via Coursera

Overview

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.

This course was offered thrice during Fall 2012, Spring 2012 and Fall 2013; in Fall of both years it was also taken for credit at IIT Delhi and IIIT Delhi. During this period, I also wrote a book to elucidate the ideas discussed in the course at a 'popular' level:

The Intelligent Web: Search, Smart Algorithms and Big Data published by Oxford University Press, UK, in November 2013.

Now in this edition, the course is being offered in 'self-study' mode.

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 Trends
Programming: Map-Reduce Learn: Classification, Clustering, and Mining, Information Extraction Connect: Reasoning: Logic and its Limits, Dealing with Uncertainty
Programming: Bayesian Inference for Medical Diagnostics Predict: Forecasting, Neural Models, Deep Learning, and Research Topics
Data Analysis: Regression and Feature Selection

Taught by

Gautam Shroff

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Reviews

2.9 rating, based on 11 reviews

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  • Anonymous

    Anonymous completed this course.

    Lections are good, but some parts are not well explained (you have to figure out some thing by yourself). But there is a very-very-very little amount of practice. But, I have to admit that programming assignment on MapReduce is cool.
  • Anonymous

    Anonymous completed this course.

    felt like a probability class than big data class. too many formulas. everything there is a formula. Not good for IT professionals.
  • Lars Ahlfors completed this course.

  • Andrei Razvan Maresu

    Andrei Razvan Maresu completed this course.

  • Rafael Prados

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  • Colin Khein completed this course.

  • Juliano Ignacio completed this course.

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