Data Science with Python: Data Analysis & Visualization

at NYC Data Science Academy

Course Details
$1,510.50 10 seats left
Start Date:

Sun, Apr 23, 1:00pm - May 21, 5:00pm Eastern Time ( 5 sessions )

NYC Data science Academy
Early bird price
Purchase Options
Class Level: Beginner
Age Requirements: 18 and older
Average Class Size: 18
System Requirements:

You will need a reliable Internet connection as well as a computer or device with which you can access your virtual class. We recommend you arrive to class 5-10 minutes early to ensure you're able to set up your device and connection.

Class Delivery:

This class will be held via Zoom unless otherwise specified

Flexible Reschedule Policy: This provider has flexible, free rescheduling for any-in person workshop. Please see the cancellation policy for more details

What you'll learn in this data science course:

This class is a comprehensive introduction to data science with Python programming language. This class targets people who have some basic knowledge of programming and want to take it to the next level. It introduces how to work with different data structures in Python and covers the most popular data analytics and visualization modules, including numpy, scipy, pandas, matplotlib, and seaborn. We use Ipython notebook to demonstrate the results of codes and change codes interactively throughout the class.


If you have good knowledge of basic data types (e.g. string, numeric), data structures (e.g. list, tuple, dictionary) and are familiar with concepts of list comprehension and for/while loop, you are good to go with the Python for Data Analysis and Visualization course. We will cover these basic Python programming topics in the course as well, but move at a relatively fast speed.


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.

  • Introduction to Ipython notebook
  • Basic objects in Python
  • Variables and self-defining functions
  • Control flow
  • Data structures

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.

  • Introduction to object-oriented programming
  • How to deal with files
  • Run Python scripts
  • Handling and processing strings

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.

  • Numpy
  • Scipy

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.

  • Seaborn
  • Matplotlib

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.

  • Pandas

Final Project

After 20 hours of structured lectures, students are encouraged to work on an exploratory data analysis project based on their own interests. A project presentation demo will be arranged afterwards.

Remote Learning

This course is available for "remote" learning and will be available to anyone with access to an internet device with a microphone (this includes most models of computers, tablets). Classes will take place with a "Live" instructor at the date/times listed below.

Upon registration, the instructor will send along additional information about how to log-on and participate in the class.

School Notes: We offer a certification licensed by the NYS Board of Education.

Still have questions? Ask the community.

Refund Policy

Note: This provider has a temporary cancellation policy for COVID-19 related cancellations which is as follows: 

Students receive a full refund of their tuition fees if they cancel their enrollment any time before the first day of the course or if they don't start the course at all (no-shows). We don't charge any registration or materials fee, and there is no charge for transferring to a future session of the course. 


Original cancellation policy (non-COVID-19):

We offer full refund if you are not happy with the first class and decide to drop it.

Start Dates (1)
Start Date Time Teacher # Sessions Price
1:00pm - 5:00pm Eastern Time TBD 5 $1,510.50
This course consists of multiple sessions, view schedule for sessions.

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Questions & Answers (2)

Get quick answers from CourseHorse and past students.

Question from Xuxinye X.
Do we need to bring a laptop, or will computers be provided? Because I have a MacBook not a PC
Answer from Daniel N. CourseHorse StaffCourseHorse Staff
No computers are provided. Students carry their own laptop. Mac book is ideal! They normally use Mac there.
Question from Xuxinye X.
If I want to sign up for the course starting 1/21/2018 - when is the deadline to sign up?
Answer from Jenn C. CourseHorse StaffCourseHorse Staff
Hi! The school allows enrollments up until 9:00 am on the first day of the class on January 21st.

Reviews of Classes at NYC Data Science Academy (31)

(31 Reviews)
Data Science with Python: Data Analysis & Visualization
Reviewed by Eli R. on 7/25/2017
This class was really enjoyable for me - it was a good way to get an introduction to a variety of very powerful Python libraries. Its certainly nowhere near as extensive as a full bootcamp, but if you're looking to be introduced to these concepts I couldn't recommend this more. I had Tony as an instructor and he was really helpful and did a great job of explaining concepts, and he took additional time to review homework solutions before class if we wanted.
Data Science with Python: Data Analysis & Visualization
Reviewed by Anonymous on 4/11/2017
I think it was a good introduction to Pandas, Numpy and Seaborn. I think a little bit too much time was spent on an introduction to Python, which I think should be a separate course so that people don't get lost and more time can be spent on data analysis. Overall, instructor was great and the class was good. I would definitely recommend if they made the changes I stated above.
Data Science with Python: Data Analysis & Visualization
Reviewed by Anonymous on 4/10/2017
This class is overall very helpful. It was a little heavier on the visualization part than I would have liked, but still good. There is a lot of material in a short timeframe, which is good overall, but it requires some time to work on and get through.
Data Science with Python: Data Analysis & Visualization
Reviewed by Maria K. on 3/6/2020
Data Science with Python: Data Analysis & Visualization
Reviewed by Ruchika S. on 3/4/2019
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School: NYC Data Science Academy

NYC Data Science Academy

NYC Data Science Academy is a program designed to teach those who wish to learn.

Through hands-on projects and real-world applications, our students develop the skills they will need to pursue data science as both a hobby and profession. We also organize the NYC Open Data Meetup, which means that by...

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