Sun, Apr 23, 1:00pm - May 21, 5:00pm Eastern Time ( 5 sessions )
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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.
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
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.
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.
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.
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.
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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.
We offer full refund if you are not happy with the first class and decide to drop it.
|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.
|Sun, Apr 30||1:00pm - 5:00pm Eastern Time||TBD|
|Sun, May 07||1:00pm - 5:00pm Eastern Time||TBD|
|Sun, May 14||1:00pm - 5:00pm Eastern Time||TBD|
|Sun, May 21||1:00pm - 5:00pm Eastern Time||TBD|
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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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