Python for Data Science

Python for Data Science

 

 
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Aim of Course:

Humans have taken their voices online en-masse. Over one billion people engage their friends via Facebook. Twitter publishes half a billion tweets each day.  In this online course, “Python for Data Science,” you will use Python to extract valuable signals from these huge, chaotic datasets to explain collective behavior and create computational knowledge bases. 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.

This course may be taken individually (one-off) or as part of a certificate program.
Course Program:

Week 1: Recommendation algorithms

  • Refresher on Python data structures
  • Streaming large datasets
  • Filtering noise in long-tailed datasets
  • Algorithmic time complexity in a nutshell
  • Introduction to recommendation algorithms
  • Case study: If you liked “Star Wars” you’ll like ??

Week 2: Introduction to text analysis in Python

  • Python’s “yield” keyword
  • Tf/Idf weighting
  • Algorithms that identify distinctive language
  • K-means clustering
  • Case study: Distinctive language in subreddit communities

Week 3: Social APIs

  • A taxonomy of social APIs and Python interfaces to them
  • Practical workflows when using social APIs
  • Case study: Datasift & sentiment analysis on Twitter

Week 4: Social network analysis

  • Network data structures in Python
  • Your Facebook graph: visualization and community detection
  • Using the Gephi network visualization tool
  • Case study: Inducing network graphs - the landscape of movies
Homework:

The homework in this course consists of short answer questions to test concepts, guided exercises in writing code and guided data analysis problems using

software.

This course also has example software codes, supplemental readings available online.


Python for Data Science

Who Should Take This Course:
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.
Level:
Intermediate
Organization of the Course:Options for Credit and Recognition:
Course Text:
All course materials will be provided during the course.
Software:
The required software is Python Programming Language.
Instructor(s):

Dates:

To be scheduled.

Python for Data Science

Instructor(s):

Dates:
To be scheduled.

Course Fee: $549

Do you meet course prerequisites? What about book & software? (Click here to learn more)

We have flexible policies to transfer to another course, or withdraw if necessary (modest fee applies)

Group rates: Click here to get information on group rates. 

First time student or academic? Click here for an introductory offer on select courses. Academic affiliation?  You may be eligible for a discount at checkout.

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Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment. Please use this printed registration form, for these and other special orders.

Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date, unless you specify otherwise.

The Institute for Statistics Education is certified to operate by the State Council of Higher Education in Virginia (SCHEV).

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