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Data Science with Python: Data Analysis


Each class is 20 hours of classroom guidance with a optional three week-long showcase project of students’ own choices and optional presentation of their projects. **You can contact for corporate training or group training if you have more than 5 people.

Course Overview

This five week course is an introduction to data analysis with the Python programming language, and is aimed at beginners.

Project Demo Day and Certificates

From the rudimentary building blocks of programming basics, to data manipulation and use of advanced drawing packages, the course ends with a demonstration of a project of your choice on Project Demo Day. On Demo Day you will access and analyze real data, utilizing the tools and skill sets taught to you throughout the course. Upon successful completion of the course and demonstration of your final project, you will qualify for one of three certificates: Extraordinary Standing, Honorable Graduation, and Active Participation. Certificates are awarded according to your understanding, skill, and participation. No prerequisite needed for the course.


1. Do I have to do three weeks project? Is it required for taking this class? Students could choose to spend extra 3 weeks with the teaching crew to do a project of their own choices. We are happy to offer assistance and arrange presentation to demo their work. 2. Can I take class online if I am not in NYC? You can take it onsite or through recorded sessions on Youtube and get timely assistance from teaching crew by google hangout or Skype. 3. If I have to miss some session, how can I make it up? We record all of our classes and make it available for students right after each class. If you miss a class, you can also get extra help such as office hour or internet support through google hangout or Skype.


Week 1 – The Python Programming Language
  • Overview of syntax, built in functions and data structures
  • Introduction to the standard library
  • Object oriented programming
Week 2 – Computational Statistics
  • Review of probability and statistics
  • Hypothesis testing
  • Introduction to Pandas
Week 3 – Data Analysis with Pandas
  • The exploratory data analysis process
  • Working with real world data
  • Data visualization with Matplotlib
Week 4 – Data on the Web
  • Web scraping
  • Accessing APIs
  • Building web applications
Week 5 – Gentle Introduction to Machine Learning
  • What is machine learning?
  • The Scikit-Learn API
  • Image Processing / Text Classification

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