Course Dates

Earlybird ends on 10/15

November Session

Nov 5 - Dec 10, 2023

Sunday, Saturday

1-5pm EDT

$1590.00

$1510.50

Enroll Now

Product Description

Course Overview

This class is a comprehensive introduction to Python for Data Analysis and Visualization. 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 Python data analysis 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.

Prerequisites

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.

Certificate

Certificates are awarded at the end of the program at the satisfactory completion of the course. Students are evaluated on a pass/fail basis for their performance on the required homework and final project (where applicable). Students who complete 80% of the homework and attend a minimum of 85% of all classes are eligible for the certificate of completion.

Syllabus

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 Tool

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

Our Alumni Feedback

Coming from the finance field, I had very little experience in coding. I had dabbled with a little bit of VBA where I worked, but by no means could I have claimed to know how to code. That being said, I feel this class provided me a great foundation to Python. The in class exercises were also helpful to glue the concepts together and homework was also given for more practice. The one thing I could have suggested in terms of the weekend class itself is to perhaps allow for a longer day so the teacher do not have to rush over any particular topic. Overall, I really enjoyed this class and would recommend it to anyone who is looking to get their hands dirty with coding and data analysis.

Raymond Liang

This was a great in-person learning experience. I have tried to learn Python using online resources for a while, but I always could not commit my time to do it. Although the class is only 5 weeks long, I feel like I learn a lot than I expected. Highly recommend this course to anyone who wants to take a well organized intro class for Python.

Jamie Huang

The weekend class is extremely helpful. You spent 5 hours on Sunday and learn as much as you could during those hours. Because it is taught by using Jupyter notebook, it is really easy to follow and to relearn over the following week. My weekend cohort consists of recent MBA grads who are looking to lead teams that work closely with software engineers and data scientists. You also see people from the risk practice of consulting/advisory companies. You can also see people who are in the IT department making a transition to the field of Data Science. Last but not least, you'll also have people in graduate school or even college who would dedicate their Sunday afternoon to refine their skills in Python. It is an investment that will pay dividends in your career if you are determined to bring some data science to your toolbox and your workplace.

Samuel Mao

I really enjoyed this class and learned a lot. As someone who already had an introductory understanding of Python, this class helped me strengthen my understanding of the fundamentals. From there I enjoyed covering a wide range of topics from Python scripting, parsing, cleaning, and graphing data. This course can be challenging because there is a new topic discussed each week, so there isn't a lot of time to refine new skills. I thought Tony was a great teacher and he always made himself available to answer questions. Overall I feel like it gave me all the tools I need to approach data science problems analytically and with confidence.

Evan Squire

This course was not only extremely cutting-edge for all of today's industries and work areas but it gave me a great deal of confidence to continue my data and computer science studies at the next level. This course has actually inspired me to not only enroll in other NYC Data Science Classes but also think longer-term about continuing graduate level work in CS. This was my first class at NYC Data Science Academy and all I an say is I am extremely grateful to have had Dr. Anthony Schwartz as an instructor. Anthony keep the material vibrant and fun with colorful analogies that made the subject matter easy to digest and remember. This allowed for both an esoteric understanding of what was happening "inside the code" coupled with real-world applications that began to streamline and automate a lot of my day-to-day work right after Class 1. I cannot day enough good things about NYC Data Science Academy and Dr. Shultz !!

Bob Trieste

I had a good time learning Python with Tony. We went through things in sufficient detail and pace. I thought the course was thorough and concise without much extra unnecessary info. I enjoyed the homework problems and thought they were challenging. I would recommend this class in the future to people looking to beef up their data analysis skills.

Naveen Ramachandran

I attended the 5 week Python course with Anthony Schultz . The syllabus was extremely comprehensive and provided a very well structured approach to Python and its applications. Anthony was a fantastic teacher and effectively covered a wide range of concepts and topics in a short time period. I enjoyed the weekly homework problems as well - they cemented what was learnt in class and really made me think. I feel a lot more comfortable in my coding abilities and would highly recommend this course.

Pranati Jain

I came across NYC Data Science Academy when I was looking for certification courses with classroom learning and I am glad I made a decision to take it up. It was a well planned course which was spread over five Sundays. Our instructor, Anthony Schultz, was extremely knowledgeable and passionate about teaching Python which made the whole course a very enjoyable experience. The course content had in depth coverage with examples to elaborate each concept, giving us the opportunity to learn as we progress. By the end of this course, you would get a good grip of Python which you can apply in your daily work.

Manjula Rimmalapudi

The course “Data Science with Python: Data Analysis and Visualization” is perfect if you are fairly new to “Data Science”. It begins with a general overview of basic knowledge in python before going to the analysis content. You will learn Numpy, Pandas, Visualization and Seaborn after you finish the course. The instructor Anthony Schultz introduced every chapter in a slow and comprehensive pace. The course notes are well organized. You can ask any questions during the class and Anthony will explain your question with great amount of details. I would love to recommend to take this class if you are planning to pursuing your career in Data Science. Five Stars!!

I took the Python: Data Analysis and Visualization class taught by Tony Schultz this summer. The course content is thorough, well formed and covered a lot of areas within the short amount of time. Tony was great with explaining all the concepts. Often times he covered more than just one way to solve a problem and encouraged us to develop our own coding styles. Definitely recommend this class to all working professionals interested in learning Data Science using Python.

Devika

I enrolled in the five-weekend course for Data Analysis and Visualization with Python taught by Tony Schultz that spanned from June to July 2019. Tony is experienced, energetic and hard working and did a great job in presenting the material. He was also very helpful before/after class answering questions related to the homework as well as more general topics related to data science. Of note I appreciated that he covered various ways of solving classroom and homework problems which helped highlight Python's flexibility. The course helped me develop a solid foundation in Python. As usual, to get the most of this class you do have to spend several hours outside of class to review the material covered in the prior class before attempting to do the homework.

Alfredo Pinel

"Great Course! Learned A lot!"

Anthony was great - really got into the practical uses of python for data analysis and had really useful analogies to understanding different topics and concepts. Really enjoyed the class and felt like I could take something practical away from it.

Nikhil Krishnan, Strategic Partnerships Manager

"Good Starter"

In the past I've used a lot of online courses to try and learn how to use python in my day to day work but I never felt like I "got it." This in person experience was well organized, provided relevant material and challenging homework. The first day of the class really scared me and had me thinking I bit off more than I can chew, but by the end I felt like I'd learned a lot and am thankful to the instructor Tony for his in class comments and examples. I would recommend this course to anyone who is already conducting data analytics but is looking to branch out to python. The course provides a lot of food for thought and made me feel like I have a solid foundation in python now.

Anthony S. Romano, Research Scientist

"Cutting-edge for all of today's industries"

This course was not only extremely cutting-edge for all of today's industries and work areas but it gave me a great deal of confidence to continue my data and computer science studies at the next level. This course has actually inspired me to not only enroll in other NYC Data Science Classes but also think longer-term about continuing graduate level work in CS. This was my first class at NYC Data Science Academy and all I an say is I am extremely grateful to have had Dr. Anthony Schwartz as an instructor. Anthony keep the material vibrant and fun with colorful analogies that made the subject matter easy to digest and remember. This allowed for both an esoteric understanding of what was happening "inside the code" coupled with real-world applications that began to streamline and automate a lot of my day-to-day work right after Class 1. I cannot say enough good things about NYC Data Science Academy and Dr. Shultz !!

Bob Trieste, Equities | FX Trader

It's important when learning anything to get the fundamentals right. If you build bad habits, it can become difficult to fix them later on, especially if you have also built many dependencies on those bad habits. This is why when I wanted to start learning about data science, I chose to take this course to help me make the right choices from the very beginning.

I would say that I got exactly what I came for. Tony is a very good instructor. He is 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

Great class. For only a 5 week class it is very comprehensive. Covers the basics and commonly used libraries used in python for data analysis as well has how to use them. Notebooks used in the class are a great go-resource after the class ends. Also a great community of data professionals and networking if you are thinking about a new gig.

Aaron Ouyang

Raymond Liang

Jamie Huang

Samuel Mao

Evan Squire

Bob Trieste

Naveen Ramachandran

Pranati Jain

Manjula Rimmalapudi

Devika

Alfredo Pinel

"Great Course! Learned A lot!"

Nikhil Krishnan, Strategic Partnerships Manager

"Good Starter"

Anthony S. Romano, Research Scientist

"Cutting-edge for all of today's industries"

This course was not only extremely cutting-edge for all of today's industries and work areas but it gave me a great deal of confidence to continue my data and computer science studies at the next level. This course has actually inspired me to not only enroll in other NYC Data Science Classes but also think longer-term about continuing graduate level work in CS. This was my first class at NYC Data Science Academy and all I an say is I am extremely grateful to have had Dr. Anthony Schwartz as an instructor. Anthony keep the material vibrant and fun with colorful analogies that made the subject matter easy to digest and remember. This allowed for both an esoteric understanding of what was happening "inside the code" coupled with real-world applications that began to streamline and automate a lot of my day-to-day work right after Class 1. I cannot say enough good things about NYC Data Science Academy and Dr. Shultz !!

Bob Trieste, Equities | FX Trader

John Chen, Software Engineer

Aaron Ouyang

Campus Location

500 8th Ave Suite 905, New York, NY 10018

Nearby Subways

1 2 3 34th, Penn Station

A C E 34th, Penn Station

N Q R B D F M 34th, Herald Square

Detailed Directions

Session Schedule

Earlybird ends on 10/15

November Session

Nov 5 - Dec 10, 2023 Sunday & Saturday

1Nov 05, 2023
2Nov 12, 2023
3Nov 19, 2023
4Nov 25, 2023

5Dec 03, 2023
6Dec 10, 2023

1-5pm EDT

$1590.00

$1510.50

Enroll Now

Save More by Enrolling in a Bundle

Data Science with Python

Introductory Python

Data Science with Python: Data Analysis and Visualization

Data Science with Python: Machine Learning

$5170.00

Total: $5170.00$4732.00

Data Science Launchpad with Python

Introductory Python

Data Science with Python: Data Analysis and Visualization

Data Science with Python: Machine Learning

$5170.00

Total: $5170.00$4770.00

Data Science with Python:
Data Analysis and Visualization

Course Dates

Product Description

Course Overview

Prerequisites

Certificate

Demo Lecture

Syllabus

Unit 1: Introduction to Python

Unit 2: Explore Deeper with Python

Unit 3: Scientific Computation Tool

Unit 4: Data Visualization

Unit 5: Data manipulation with Pandas

Our Alumni Feedback

"Great Course! Learned A lot!"

"Good Starter"

"Cutting-edge for all of today's industries"

"Great Course! Learned A lot!"

"Good Starter"

"Cutting-edge for all of today's industries"

Campus Location

Session Schedule

Save More by Enrolling in a Bundle

NYC Data Science Academy

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