Analytics in Python


Data is the lifeblood of an organisation. Competency in programming is an essential skill for successfully extracting information and knowledge from data. The goal of this course is to introduce learners to the basics of programming in Python and to give a working knowledge of how to use programs to deal with data.

In this course, we will first cover the basics of programming and then focus on using Python on the entire data management process from data acquisition to analysis of data big data and small data.

This is an intensive hands-on course that will equip and reward learners with proficiency in data management skills.

Associated Programmes: Business Analytics MicroMasters® Programme

Business Analytics MicroMasters® Programme
Columbia’s MicroMasters® programme in Business Analytics will empower learners with the skills, insights and understanding to improve business performance using data, statistical and quantitative analysis, and explanatory and predictive modelling to help make actionable decisions.

Analytics in Python
Learn the fundamental of programming in Python and develop the ability to analyse data and make data-driven decisions.
View the course

Data, Models and Decisions in Business Analytics
Learn fundamental tools and techniques for using data towards making business decisions in the face of uncertainty.
View the course

Marketing Analytics
Develop quantitative models that leverage business data to forecast sales and support important marketing decisions.
View the course

Demand and Supply Analytics
Learn how to use data to develop insights and predictive capabilities to make better business decisions.
View the course

Prerequisites: Prior exposure to some programming language is helpful but not necessary.

edX® is a registered trademark of edX® Inc.  All Rights Reserved.

  • Programme duration
    12 weeks
  • Estimated effort
    8 to 10 hours per week
  • Fee
  • Institution
  • Language
Start Dates
  • Become familiar with working with relational databases, using SQL based languages such as MySql, dealing with formatted data (XML, JSON, etc.)
  • Use Python to work with and analyse data from databases as well as from the web
  • Use Big Data processing frameworks like Hadoop and MapReduce