[su_tab title = “Description”]
Over one billion people engage their friends via Facebook. Twitter publishes half a billion tweets each day. In this online course, you will use Python to extract valuable signals from these huge, chaotic datasets to explain collective behavior and create computational knowledge bases.
[su_tab title = “Program Structure”]
Using Python, you will analyze user-generated content such as movie ratings, online comments, status updates, and friendship networks. You will learn algorithms from the fields of social network analysis, text analysis, and recommender systems. Finally, you will gain experience with pragmatic workflows that leverage social APIs to reveal human insights in your own projects.
- Week 1: Recommendation algorithms
- Week 2: Introduction to text analysis in Python
- Week 3: Social APIs
- Week 4: Social network analysis
September 18, 2015 to October 16, 2015
About 15 hours per week, at time of your choosing.
INR 32,940 (assuming $ = INR 60)
Part Time/ Full Time:
[su_tab title = “Eligibility”]
These are listed for your benefit so you can determine for yourself, whether you have the needed background, whether from taking the listed courses, or by other experience.
- Introduction to Python for Analytics
Programmers and statisticians familiar with Python who want to learn how to do analysis of text and social network date; analysts who know some Python and who want to deepen their Python knowledge by learning how to mine social data.
[su_tab title = “Tools”]
[su_tab title = “Faculty”]
- Dr. Shilad Sen
[su_tab title = “Contact”]