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Python for Data Science Bootcamp

Hands-on Python Bootcamp in NYC

Data is growing in importance across every industry, and Python has become far-and-away the most popular tool for doing advanced data analysis.

In this hands-on course, students will quickly go from learning the fundamentals of Python to analyzing real-world datasets. The initial classes will give students practice with foundational programming concepts like loops, functions, and objects. The focus of the class will then shift to tabular data, as you find in CSV files or databases. You will learn how to clean and combine data, as well as generate useful statistics and visualizations. The final sessions will be focused on using linear regression to extrapolate from data and make predictions. For more information about the topics covered in the course, please refer to our syllabus below.

This course is designed to give beginners the practical skills they need to start contributing valuable insights for their company or organization. Examples and exercises will emphasize how these techniques can be applied to real-world situations and use cases. Previous math or coding experience is not required.

Instructor Bio: Rob joins Noble Desktop after years of experience in the FinTech industry, where he worked on data analytics tools for banks and credit unions. Most recently, he was a senior developer on a targeted marketing tool which won an industry-wide innovation award and is now used by over 80 institutions. Rob holds a B.A. in Mathematics from Wesleyan University and a M.Sc. in Mathematical Logic from the Universiteit van Amsterdam.

Still Have Questions?

Want to discuss this class further? Email the program director directly and find out if this is the right course for you.

  • Small Classes
  • Computer Provided
  • Top Instructors
  • Free Retake

Take this class as part of a certificate program and save:

  • 3D stats model

    Learn how to create impressive data visualizations

  • 2 graphs

    Learn to take cross-sections of your data and find patterns

  • gold prices

    Learn to graph commodity prices and other kinds of timeseries data

  • double line graph

    Learn to overlay and compare trends in your data

  • heat maps

    Learn to customize your visualizations with vibrant color schemes

NYC’s Best Python Bootcamp

In this hands-on course, students will learn to use Python as a powerful and flexible tool for data analysis. The curriculum will cover every step in the process of turning raw data into useful graphs, reports or statistics. Students will leave this course with the ability to write Python scripts to collect, clean, and visualize data. With data taking on larger importance across all industries, this course has something to offer for anyone working in business, technology, academia, or entrepreneurship.

  • “The Python for Data Science course was a mix of theory and hands on application. Probably the best value class out there.”

    Lorela Blaka

  • “Great Class. I would highly recommend this class. ”

    April E Cooke

  • “Rob is very helpful and always ready to answer questions. He explained the content very well. The course is a great introduction to Python and programming!”

    Leyla Beck

  • “A complex subject, clearly broken out into simple steps.”

    James Siwicki

  • “Course content was more than adequate and very applicable to Data Science and analysis. Learned a lot of takeaways that I will apply at work.”

    Melissa Manganaan

  • “Having no prior knowledge or experience in computer/data science, I feel as though this course prepared me well in order to use and apply Python through a thorough, yet understandable curriculum.”

    Gabriel Kerstein

  • “At worst, this class will get you from knowing NOTHING about coding to a point where you are proficient enough to understand what Python can do and how to apply it to your job.”

    Alex

  • “"Great class for someone who wants to get out of their comfort zone and challenge themselves to pick up a new skill"”

    Tanuja Pulakhandam

Frequently Asked Questions

  • Do you need to come in with any prior math or programming knowledge?

    Prior math or programming experience is not required for this course.

  • How is this class structured?

    The first 12 hours of this class covers Python the language and general computer science topics. The following 18 hours covers data science topics such as descriptive statistics, data importation, graphical representation of data, and forecasting models.

  • How many students are in a given class?

    Noble's typical class ranges from 8-12 students, but we allow up to 20 students to register for our course.

  • How does this class prepare me for the job market?

    The classes will prepare students with proficiencies in Python and its data science libraries. This is a great starting point for any looking to pursue a career in data science and a perfect class for students looking to add complementary skills to their current job or resume.

  • Why do you need to learn NumPy, Pandas, Matplotlib, and Sci-Kit Learn?

    Each library allows Python to be used for different tasks. The NumPy package is the foundational package for all of data science as it allows Python to do both mathematical and statistical operations. Pandas allow Python to work with tabular data such as data imported from CSV or Excel file. Matplotlib package is a tool that allows for Python to have graphing capabilities similar to Excel. Lastly, Sci-Kit Learn allows for regressional and predictive analysis of data.

  • Is there mandatory work outside of the classroom?

    Students are not required to complete any work outside of class. However, we provide students with bonus materials if they would like extra practice.

  • What tangible skills do students leave with after the class?

    Students will leave with proficiencies in both Python. Additionally, students will be proficient in various Python libraries such as NumPy, Pandas, Matplotlib, and Sci-Kit learn. These libraries will allow students to automate data collection, perform analysis on the data, graph the data, and use this data to create predictive models.

  • Do you offer discounts or a payment plan for this course?

    Discounts
    • 10% Alumni Discount: Get 10% off this course if you’ve previously taken any 12+ hour course.
    • $100 Individuals Discount: Take $100 off this course if you’re an individual paying for yourself (you’re not being reimbursed by a company).

    Discounts are applied at checkout (no promo code required) and will be verified after you place your order. Discounts are subject to change. Read our discount policies for more details.

    Payment Plan

    This course is not eligible for a payment plan, which is only available for programs priced at $2,495 and above. Read our Payment Plan FAQ for more details.

    Take this course as part of a certificate program and save:
  • Can I take this course online (remote learning)?

    You may attend this training virtually (online) at the scheduled time the course is offered (New York, Eastern Time).

    How does attending “live online” work?
    • Students can attend this training remotely through screen sharing software (we use Zoom).
    • Participants can hear the instruction, ask questions, and even share their screen with the instructor.
    • For audio you can use your computer’s microphone/speakers or call a phone number that we’ll provide.
    • Classes are activity-based and taught by a live instructor, so we strongly encourage students who are local to the area to attend in person!

Expand Your Skills with Data

In this class, students will learn to use Python as a powerful tool for data analysis. Learn to combine and query on thousands of rows of data, pulled from an array of sources such as Excel files, CSVs, and APIs. 

Student learning to use Python for data analysis

Hands-on Python Training

In our Python classes, students will dive into coding within the first 10 minutes. After introducing concepts and demonstrating them in code, the instructor will help you though hands-on exercises like cleaning a data set, creating graphs and analyzing stock market data.

Student coding Python for data science