Web Intelligence and Big Data

Gautam Shroff, Indian Institute of 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. In the past, this course has been offered at the Indian Institute of Technology Delhi as well as the Indraprastha Institute of Information Technology Delhi.

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.


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

Recommended Background

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

Course Format

The course consists of lecture videos, which are between 5 and 15 minutes in length, adding up to a maximum of 1-1.5 hrs per week. There are 1-2 integrated quiz questions per lecture video. Additional short quizzes will test basic understanding. However, the current edition of the course is being offered in 'self-study' mode, so there are no homeworks, assignments or exams. Nor is there active support by the instructor or TA, but discussion forums are available for peer-learning.


  • Will I get a certificate after completing this class?

    No. In the past, statements of accomplishment were given. However,  the current edition of the course is being offered for 'self-study', without any graded homework or exams, and so no certificates.

  • 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. See http://www.python.org.

  • 20 апреля 2014, 9 недель
  • 26 августа 2013, 12 недель
  • 24 марта 2013, 10 недель
  • 27 августа 2012, 10 недель
Характеристики онлайн курса:
  • Бесплатный:
  • Платный:
  • Сертификат:
  • MOOC:
  • Видеолекции:
  • Аудиолекции:
  • Email-курс:
  • Язык: Английский Gb


Пока никто не написал отзыв по этому курсу. Хотите быть первым?

Зарегистрируйтесь, чтобы оставить отзыв

Входит в подборки курсов:
Small-icon.hover Machine Learning
Machine learning: from the basics to advanced topics. Includes statistics...
Ещё курсы на эту тему:
68688_8395_10 Microsoft SQL Server 2012 Certification Training Exam 70-463
Study For Implementing a Data Warehouse with Microsoft SQL Server 2012 (Exam...
Chico-compy-v2 Big Data in Education
Education is increasingly occurring online or in educational software, resulting...
65522_3a49_5 Information Retrieval and Mining Massive Data Sets
Learn various techniques to build a Google scale Information Retrieval System...
40684_d8c2_5 Data Organization - Learn Big Data Management - Udemy
Infrastructure, Algorithms, and Visualizations
15-062s03 Data Mining
Data that has relevance for managerial decisions is accumulating at an incredible...
Ещё из рубрики «Компьютерные науки»:
Maxresdefault CS 282: Principles of Operating Systems II: Systems Programming for Android
Developing high quality distributed systems software is hard; developing high...
Banner_ruby Ruby on Rails Tutorial: Learn From Scratch
This post is part of our “Getting Started” series of free text tutorials on...
Logo-30-128x128 NYU Course on Deep Learning (Spring 2014)
Lectures from the NYU Course on Deep Learning (Spring 2014) This is a graduate...
Cppgm C++ Grandmaster Certification
The C++ Grandmaster Certification is an online course in which participants...
Umnchem Computational Chemistry (CHEM 4021/8021)
Modern theoretical methods used in study of molecular structure, bonding, and...
Ещё от Coursera:
Success-from-the-start-2 First Year Teaching (Secondary Grades) - Success from the Start
Success with your students starts on Day 1. Learn from NTC's 25 years developing...
New-york-city-78181 Understanding 9/11: Why Did al Qai’da Attack America?
This course will explore the forces that led to the 9/11 attacks and the policies...
Small-icon.hover Aboriginal Worldviews and Education
This course will explore indigenous ways of knowing and how this knowledge can...
Ac-logo Analytic Combinatorics
Analytic Combinatorics teaches a calculus that enables precise quantitative...
Talk_bubble_fin2 Accountable Talk®: Conversation that Works
Designed for teachers and learners in every setting - in school and out, in...

© 2013-2019