Data Science with Python Course

Data Analysis and Visualization with Python 


This is a 5-week comprehensive introduction to Data Analysis and Data Visualization using the Python programming language.


Notice: This course is currently being delivered live online at this time.

Find out how this course looks like. Watch a clip of a sample lecture by completing this form.

Unit 1

Introduction to Python

Python is a high-level programming language. You will learn the basic syntax and data structures in Python. We demonstrate and run codes within Ipython notebook, which is a great tool providing a robust and productive environment for interactive and exploratory computing.

Unit 2

Explore Deeper with Python

Python is an object-oriented programming (OOP) language. Having some basic knowledge of OOP will help you understand how Python codes work. More often than not, you will have to deal with data that is dirty and unstructured. You will learn many ways to clean your data such as applying regular expressions.

Unit 3

Scientific Computation Tools

There are two modules for scientific computation that make Python powerful for data analysis: Numpy and Scipy. Numpy is the fundamental package for scientific computing in Python. SciPy is an expanding collection of packages addressing scientific computing.

Unit 4

Data Visualization

Python can also generate graphics easily using “Matplotlib” and “Seaborn”. Matplotlib is the most popular Python library for producing plots and other 2D data visualizations. Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing statistical graphics.

Unit 5

Data Manipulation with Pandas

Pandas provides rich data structures and functions for working with structured data. The “DataFrame” object in Pandas is just like the “data.frame” object in R. Pandas makes data manipulation (filter, select, group, aggregate, etc.) as easy as in R.

Final Project and Certification

Final Project

Students are encouraged to work on an exploratory data analysis project based on their own interests. A project presentation demo will be arranged after the course. Certificates are awarded at the end of the program at the satisfactory completion of the course.


June Session

Saturdays, June 13 - July 18, 2020 
1:00 pm - 5:00 pm

August Session

Sundays, August 2 - August 30, 2020 
1:00 pm - 5:00 pm


"As a novice coder, this class was a great way to learn how I can manipulate and analyze data in Python. Would recommend for anyone interested in learning how to use python and apply to daily work."

Matt Gray
Manager, Corporate Strategy at NBC Universal

"I would say that I got exactly what I came for. They have very good instructors. They were able to express complicated concepts in an understandable way, and I would definitely say that now I understand enough about the Python ecosystem that I could start learning on my own if I wanted."

John Chen
Software Engineer at American Express

"The exercises in class and the homework got our hands dirty with the language and the final project was a great way to create a real result by the end of the course. Overall it was challenging, but a valuable intro to a useful tool that was easier to approach with real-life sessions than self-study demos on my own. I’ll definitely take classes with NYC Data Science Academy in the future and would recommend it to my friends."

Sasha Bartashnik
Senior Manager, Marketing Analytics at Zulily


Hasan Aljabbouli is an Assistant Professor in Computer Science. He obtained his Master's and Doctorate in Artificial Intelligence from Cardiff University in the United Kingdom and his Bachelor's in Engineering in Information Technology from Homs University. He worked for different universities and has published many scholastic materials in Data Mining and Machine Learning and its applications. In addition to his academic experience, Hasan received two patents and earned relevant experiences participating in various technical projects.


Alex Baransky received his degree in Environmental Biology from Columbia University. He has experience with multiple computer languages including Python, R, and SQL. As an engineer at heart and biologist through training, Alex is passionate about animal behavior and finding innovative ways to use data science in the field of biology.


Learn Data Analysis and Visualization with Python

Get a comprehensive introduction to Data Analysis and Data Visualization using the Python programming language today. 

Find out how this course looks like. Watch a clip of a sample lecture by completing this form.