Featured Python Bootcamps

Learn Python for data science, web development, machine learning, or FinTech. Choose the bootcamp that meets your learning goals.

Data Science Certificate
- Saturdays, weekdays, or evenings
- 114 hours
- Open to beginners
- Financing available
- 1:1 Mentoring
Learn Python, SQL, automation, and machine learning to become a Data Scientist. Gain Python programming, data analysis, SQL querying, and predictive modeling skills. Perfect for beginners, this program prepares you for entry-level data science and Python engineering roles. Unlock high-paying job opportunities in the field of data science.

View course
Compare
Python Developer Certificate
- Weekdays only
- 90 hours
- Prerequisites required
- Financing available
- 1:1 Mentoring
Learn the skills needed to become a Python Developer, from Python programming fundamentals to web development with Django and Django REST. Develop in-demand skills with Django, a popular Python web framework used for back end web programming, and build a portfolio of projects under the guidance of the lead instructor.

View course
Compare
Python for Data Science Bootcamp
- Saturdays, weekdays, or evenings
- 30 hours
- Open to beginners
Unlock the power of Python for data-driven decision-making as you master Python programming fundamentals and dive into data analysis. Acquire essential skills to clean and manipulate data, create insightful visualizations, and perform statistical analysis, all through hands-on projects with real-world datasets.

View course
Compare
FinTech Bootcamp
- Saturdays, weekdays, or evenings
- 114 hours
- Open to beginners
- Financing available
- 1:1 Mentoring
Get the skills you need for a career in finance technology with the FinTech Bootcamp. Learn Python programming, data science, financial analysis, data visualization, and machine learning to become a Financial Analyst, Data Scientist, or Data Analyst.

View course
Compare
Python Machine Learning Bootcamp
- Weekdays, evenings, or saturdays
- 30 hours
- Prerequisites required
Learn the fundamentals of machine learning, including regression analysis and classification algorithms, in this practical, hands-on course. Gain the skills needed to solve real-world problems using machine learning, with a focus on Python programming and data science libraries.

View course
Compare
Python Data Science & Machine Learning Bootcamp
- Saturdays, weekdays, or evenings
- 96 hours
- Open to beginners
- Payment plan available
- 1:1 Mentoring
Master Python for data analysis, machine learning, and automation. Build predictive models, create dynamic dashboards, and unleash the power of data visualization. Launch your career in data science and Python engineering, equipped with Python, NumPy, Pandas, and Matplotlib.

View course
Compare

See All Python Courses

Learn the Most Powerful Programming Language

Launch your career as a data scientist or analyst. Our modular approach makes learning more affordable and easy to build on. You can start with our introductory Python and SQL courses and earn a certificate over time. You only take the classes you need to increase your earning potential, gain in-demand skills, and embark on a career in a new line of work!

Learn Real-World Design & Coding Skills

“Noble Desktop is far and away the most efficient way of gaining computer graphics skills. They give real-world exercises to work on, teach best practices, and inspire many an ‘aha!’ moment. Highly recommended.”
Joanne Hu
30 Years of Experience

Since 1990 we have perfected the craft of teaching. If students get hung up on an issue, we tweak the class to make it better. We’re the longest running independent training center for code and design in NYC.

Highly Reviewed by Our Alumni

From our hands-on training style to world-class instructors and proprietary curriculum, we deliver a learning experience our alumni can be proud of.

Our Python Bootcamps are rated 4.7 stars by 531 students

in the past 24 months

Very useful instructors and good content. Would recommend the Python Machine Learning Bootcamp.

Roberta Caselli

Throughout my career, I've had several technical training sessions before this one. Boris was the most knowledgeable and clear instructor I've ever come across. I'll be requesting additional Python training in 2023 and would love to work with him again.

Jason Vandervoort

This was easily the best instruction I have received all year -- I honestly feel like 3 days was enough time to get the entirety of Python's basics down, and I am looking forward to actively pursuing this as a data language. Boris was a fantastic teacher with excellent pacing and an easy-to-understand style, and the class materials were laid out in a sensible manner to pack a lot of content into a few short days of instruction.

Zachary Rusconi

It was great to see my progress during the duration of this bootcamp. I started with no prior knowledge of Python and by the end of the course, I was able to complete a machine learning project using Python.

Niekel Griffith

In just one week, I went from knowing nothing about Python to being able to code in numerous ways. This virtual course did a wonderful job feeling like an in-person course and we had an engaging teacher.

Merianne Spencer

I am learning what I wanted and in the right atmosphere with the right instructor. Art understands Python and knows how to drive its juice into our souls. He is patient and tolerant with us and has so many ways to make each format sink in.

Jesse Daniels

I highly recommend the Python for Data Science Bootcamp to anyone who has little programming experience and would like to know some basic knowledge about Python.

Yulei He
Centers for Disease Control and Prevention

I hope I can take another class with Art!

Dieudonne Nahigombeye
Centers for Disease Control and Prevention

Whether you are a beginner, slow learner, or intimidated by coding, this class will ease your fears.

Amanuel Melekin
Centers for Disease Control and Prevention

Terrific curriculum and content, and a world-class instructor and hands-on practice. Couldn't have asked for a better overall experience. 10 stars out of 5!

Jordan Fogel

Had a great experience and learned a lot within such a short period of time.

Russel Rouf

Very useful instructors and good content. Would recommend the Python for Data Science Bootcamp.

Roberta Caselli

I recommend this course, this teacher, and this school to everyone wanting to learn machine learning. It was an amazing experience.

Federico Garay

A fast-paced bootcamp that kept me engaged and was kept lively with humor.

Robert McLoughlin

Excellent materials and quality of instruction. I came away feeling confident in what I knew and with lots of detailed notes that I could refer to in the future. Probably the best virtual instruction that I've attended!

Leron Culbreath

I thought the content for the class provided good coverage of the foundations of Python. Art is a good instructor. I like his approach of teaching a concept, then giving us an exercise to work through.

Michael M.

Instructor was very good. Clearly walked through a broad amount of Python material in a succinct and helpful way.

Peter B.

I think of this as one of those "teach a man to fish" classes in that I am confident I can now: a) independently further build my class project app, and b) create a new app from scratch. If you're reading this, you've probably worked through some coding tutorials but still don't know how to put it into use or what skills and knowledge you're missing to build your own app. This course walks you from point A to point Z, building a sample app as a class, then working independently on your own project idea. The sample app teaches you the basics while your own project allows you to explore your own interests and get assistance on it from the instructor. Because of this class I now think of programming as my weekend hobby for pet projects as opposed to something I'm trying to force myself to learn.

Michael McGill

Excellent. Art fine-tunes his teaching style to our level of understanding. Efficient, patient, current examples of data topics, overall great for me as a beginner - never coded at all prior!

Michelle Moreno

Art is a very helpful and patient instructor. I'm amazed at what I can build now.

Daniel Laserna

The 5-day Python bootcamp was excellent! It was exactly what I needed to get a broad overview of Python, and it got me excited to continue coding. The course instructor Brian was fantastic. He kept the class fun, interesting, and engaging. I really enjoyed his teaching style.

Rasia Naidoo

The teacher really cared and was enthusiastic, I'm glad I took the course. The prepared Python files are really nice. Having a "start" and "finish" version is also really nice. Can't stress enough how great it is to have extra exercise files directly related to what we covered but going in more depth than we have time for to work on afterward.

Chris Greene

Art transfers his knowledge very successfully. The Python Machine Learning Bootcamp included a lot of examples, practice, and possibilities for learning.

Nikola Janjic

Art did an excellent job of helping us to understand Python!

Loyce Laurent

Excellent coursework and professor. It helped me grasp the basics of machine learning quickly and effectively. The class was hands-on and helped me implement Python concepts and apply them to build machine learning models. It was a great learning experience!

Jayashree Subramanian

Rob was absolutely fantastic. I have done other training sessions (not with Noble) and he has been by far the best. He was entertaining, patient, and had a true mastery of the subject matter. A great teacher!

David

Excellent class. By the end of the day, we understood how to scrape a website for information and send results by email, text, or saved to the local computer. Highly useful.

Rahmaan Mwongozi

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

Lorela Blaka

Was a great intro for someone looking for a Python introduction with clear use cases.

Kate Binder
FCBNY

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

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

Tanuja Pulakhandam

Great introduction class! Excellent learning environment and teacher.

Manvi

I learned so much in just a span of two weeks. Very awesome experience.

Isaac Amar
NA

This class teaches real world uses for computer science languages

Soham Bafana

Great Class. I would highly recommend this class.

April E Cooke
JPMorgan Chase

Noble Desktop is definitely one of the best courses I've taken. Class was so informative and interactive, I will definitely come back.

Joyce Li

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

A complex subject, clearly broken out into simple steps.

James Siwicki

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

I learned so much in only one week. I highly recommend this class.

Arthur

Great way to start learning Python!

Nolan Young

Enrolling in the Python for Data Science course was the best decision I could have made for myself and my advancing career. I'm feeling confident enough to move beyond my traditional role using what I've learned at Noble Desktop to create a portfolio of my knowledge.

Aja Walton

Really great way to jump into a complicated topic.

Nolan Young

I highly recommend this class to anyone that is looking for an intro to machine learning.

Marcelo Zampietro

Rob is extremely knowledgeable and made learning a complicated subject matter more accessible

Jason Alter
Tapestry Inc.

Noble is the best. Period.

Andrew Ortiz
JP Morgan Chase

I feel very comfortable with the Python syntax after taking this course...I had zero previous experience.

Philip E Camp
FEMA

Highly recommended course and the instructor is detail oriented and knowledgeable!

Yamini Y
American Express

Professional, supportive, engaging and down to earth instructors. Noble Desktop is always there for you.

Mai Amouyal

If you're truly starting with just about zero programming experience this particular Bootcamp will catapult you into intermediate within a few short weeks. Before the class was over I was already able to complete projects on Coursera's project series with relative ease. To be able to cover loops, numpy, pandas, and even data visualization in a short time is very impressive.

Tyler Irwin
New York Life

EXCELLENT! I was surprised by just how 'inspiring' Patrick turned out to be. He made the material interesting and provided a model of how to establish a good mind-frame necessary to mastery. I loved it. Felt like I got personal direction as well as technical skill.

Sean Kerr

This is a great crash course for anyone who's worked with basic Python files and wants to know what they're reading, and to start writing scripts of their own.

Gabe Scelta
United Nations

Thalo is a great machine learning instructor. He takes his time to make sure you have good notes and explains everything so that you are not left behind.

Mayhugh Davis

As an experienced analyst looking to expand my skillset to include Python, this class was ideal. Without having any Python experience I am now confident I can start leveraging it in my day-to-day work. The class covers everything from how to install and access Python, to data manipulation and visualization.

Harry S Vanderburg
ABILITY Network

Learn More About Python

Python is a general-purpose programming language that can be used to develop applications, analyze and visualize data, create machine learning algorithms, automate tasks, and much more. Initially released in 1991 by Guido van Rossum, Python is open-source and emphasizes readable and efficient code, while being flexible and scalable.

Through various frameworks and libraries, Python has extensive applications in areas such as data science, software development, machine learning, and scripting. Due to its flexibility and efficiency, Python is the “most wanted” programming language for the second year running, according to the most recent survey by Stack Overflow.

Python for Data Science

Python is the most commonly used programming language in data science—with almost 70% of data scientists reporting that they use it. It has surpassed R for the number one spot and has maintained this position due to its ease of use, powerful libraries and packages, clear and user-friendly documentation, and abundant community support.

Python is easier to read and write than most other general-purpose languages, especially for analytical computing and quantitative data analysis. Data scientists are already handling complex analysis of data, so they don’t need their programming language to be complicated, too. Python is known for its simple syntax and ease of use—even for beginners.

Python is open-sourced and has numerous libraries and packages available for data science. While some other languages (like Ruby) have clean and simple syntaxes, they don’t offer the same variety of scientific computing and machine learning libraries as Python.

There are thousands of libraries in the Python Package Index. Some of the most useful libraries and packages are Pandas, NumPy, Matplotlib, and Sci-Kit Learn.

NumPy

NumPy is a powerful linear algebra package for Python. It is primarily used for scientific computing. Many other libraries (Pandas, Matplotlib, and Sci-Kit Learn, for example) are dependent on NumPy. NumPy has extensive documentation and can be installed quickly and easily.

NumPy works with multi-dimensional arrays in Python. Lists can be converted into arrays, random arrays can be created, and numerous operations can be performed on these arrays. This is a crucial feature because operations (addition, subtraction, multiplication, and division, for example) cannot be performed on standalone Python lists, but they can easily be performed on NumPy arrays. Since data scientists often need to perform operations on data sets, NumPy is an invaluable tool.

NumPy allows you to find the min, max, standard deviation, and variance on an array. It allows you to combine different arrays to form a single array.

Overall, NumPy arrays are faster, easier to use, and use less memory than Python lists. When working with massive data sets, convenience and ease of use are two big selling points.

Because arbitrary data types can be defined with NumPy, the package is able to connect with a variety of different databases. This adds to its versatility and makes it an important component of any data scientist’s technical repertoire.

Pandas

Pandas is an open-source library that provides high-performing, user-friendly data analysis tools for Python. It is one of the most popular libraries and, as such, has excellent documentation.

Pandas essentially takes data (from a CSV file or a SQL database, for example) and creates a Python object called a data frame. A data frame organizes data in a format that resembles a table, so it is easy to read, easy to analyze, and easy to work with.

Pandas is dependent on NumPy, and can optionally be used with Matplotlib for data plotting and visualization. Because of this, it can be installed on its own, or it can be installed through a package like Anacondas, which will install all required dependencies.

Pandas is usually used in one of three ways:

To convert a list, dictionary, or array into a data frame
To open a local CSV file or a related data file
To open a remote file (CSV, JSON, SQL database, etc.)

After opening the file that you’d like to work with, you can perform a number of different commands to analyze the data. You can perform statistical analysis (mean, median, standard deviation, and so on), you can retrieve specific data points, and you can file, sort, or group data as you see fit.

Another important feature is the ability to clean data by checking for null values within the data set. It is difficult to work with data that has not been cleaned; unintentional null values within data sets can skew your results or make the results difficult to analyze. Pandas addresses this concern by identifying pieces of data that might be missing, incomplete, or otherwise incorrect so that you can get the most accurate results from your analysis.

Matplotlib

Matplotlib is another popular library that allows data scientists to visualize data. Data visualization is a crucial step in making data accessible. It allows you to identify outliers and patterns quickly, while making data interpretation easier overall. Research shows that people in general are very receptive to visual representations of data, making Matplotlib an invaluable resource in data science.

Matplotlib is free, easy to install, and has robust features. Data can be rendered as a histogram, a pie chart, a line graph, a box plot, and so on. There are enough features to satisfy advanced users, but even entry-level users can create powerful visualizations of data.

Consider an enormous data set that encompasses countless data points over a long period of time. While this data can be displayed in an array or in another numerical format, it would take awhile to read and analyze. There is a potential for human error when manually reading and interpreting massive lists of data. Naturally, human error is something that data scientists try to avoid.

Matplotlib allows you to choose the specific data that you’d like to work with and arrange it in any visual format that you can imagine. Data can be rendered and displayed in almost any format with a few quick commands. Because Matplotlib is so easy to use and works seamlessly with other Python libraries and packages, it is a top choice for data scientists who use Python.

Sci-Kit Learn

Many data scientists begin their analysis and evaluation of data with Pandas before moving over to Sci-Kit Learn for machine learning. Sci-Kit Learn is a machine learning library for Python that works with NumPy arrays and focuses on modeling data, not operating on it (NumPy and Pandas handle this).

Some modeling options include clustering, data sets, parameter tuning, and cross-validation. Sci-Kit Learn comes with standard data sets (for classification and regression of data, for example). Sci-Kit Learn is used in conjunction with stats and linear regression to make predictions based on data sets.

Other Libraries and Packages

These libraries and packages, among others, are one of the main reasons that Python is so popular in data science. The options to import, manipulate, operate on, clean up, visualize, and model data are unmatched by any other programming language’s libraries.

In our Python for Data Science Bootcamp, we cover Python in depth, and we hone in on NumPy, Pandas, Matplotlib, and Sci-Kit Learn to help you make the most of your data.

Python for Machine Learning

One of the most powerful tools of Python is its machine learning capabilities. Machine learning is a subsection of artificial intelligence that creates programs to automate data analysis and learn from the data. This is a remarkably powerful tool because as data continues to grow and become more complex, machine learning algorithms will be able to produce full-scale automated models that are efficient and reliable.

Python is the number one language used in machine learning projects due to its simplicity, wide-usage, and open source packages, like scikit-learn. Scikit-learn is a machine learning library built for Python that allows programmers to cluster data and run various forms of modeling algorithms on the data.

Sci-kit learn has much to offer when it comes to machine learning due to its simplicity and flexibility. In as few as two-lines of code, an analyst can run a decision tree model on a massive data frame in seconds!

However, the main reason scikit-learn is the gold standard for machine learning is that it’s built on top of several common Python libraries, which allows programmers to input Numpy arrays and Pandas data frames into scikit-learn. Additionally, scikit-learn provides programmers with a full suite of data modeling tools such as Regression, Decision trees, Neural Networks, SVMs, and Naive Bayes.

Python for Software Development

As the number of websites, daily active users, and applications grows, programmers are increasingly turning to Python for software development. Python was designed for server-side web applications for its easy integration with other languages and its flexible frameworks,

One of Python’s benefits is its easy integration with other web languages. Python has third-party packages that enable collaboration with other languages such as C, Java, Ruby, and Objective-C. This allows for quick development and deployment of particular parts of tools and applications.

Python’s web frameworks, namely Django and Flask, allow programmers to create and scale projects efficiently.

Flask is a relatively new framework, and is now the most commonly used web framework for new Python coders. Flask is simple and easy to learn due to its lack of syntax and need for boilerplate code. This minimalistic language allows for a great deal of control and is the ideal choice for websites that provide live updates, for example, a stock ticker, due to its speed and live data fetching abilities.

Django is a “batteries included” framework, which means that Django makes it easy for Python developers to dive into web applications without worrying about the infrastructure upfront. Django is a well-established platform that supports many plug-ins, but it unfortunately has a steep learning curve and can feel overwhelming for new programmers.

Web Development is another vertical that displays Python’s flexibility and power. Whether you want to create software, websites, web applications or just learn how to code, Python is the perfect language to choose!

Python for Automation

Python’s power extends beyond data science, machine learning, and web development, and makes its way into automation. With the power of Python, programmers can automate tasks that, for decades, had to be manually completed. Python scripts are capable of automating countless types of tasks due to the extensive libraries that are available in the language.

One of the most popular automated tasks in Python is called web scraping. Using Beautifulsoup, programmers are able to write a Python script that will “scrape” the data off a webpage and store it into a CSV file. This allows researchers to gain all the information they are seeking in a clean, easy-to-analyze format within seconds!

Python can be used to automate hundreds of additional tasks such as inputting data into a form, searching for files, updating data in Excel, and much more. Through the power of automation, Python enables programmers to complete tens of hours’ worth of tedious tasks in just a few seconds.

Learn Python for a New Career

Python Developer source: indeed.com

Salary in NYC

$124,000 / year

Python Developers typically choose to focus on back end web development, data science or analysis, scripting, or product development. They build the server side of websites, processes for data analysis, and create automation scripts.
Data Scientist source: indeed.com

Salary in NYC

$127,000 / year

Data scientists collect, organize, and analyze large sets of data, providing analysis that is key to decision making. Governments, non-profits, and businesses of all types rely on data for forecasting, risk management, and resource allocation. Data scientists discover and analyze trends in data, and report their findings to stakeholders. They will use algorithms and models to simplify and mine data sets to create data-driven recommendations. Data scientists are needed across a handful of industries, especially the ubiquity of data and the reliance on it for business decision-making.
Web Developer source: indeed.com

Salary in NYC

$93,000 / year

Web developers build webpages using coding languages such as HTML, CSS, and JavaScript. They program functionality and identify/troubleshoot errors in code. Web developers can work on front-end development (the part of the website you see in a web browser), or on back-end development (the logic and database functionality that runs on the web server). Others work as full-stack developers, providing end-to-end (front to back) expertise.
Full Stack Developer source: indeed.com

Salary in NYC

$132,000 / year

Full Stack Developers build web applications for both the visible front end that users see and the back end that powers the applications.
Back End Developer source: indeed.com

Salary in NYC

$153,000 / year

A Back End Developer builds the server-side of a web application and integrates front end development components.
Product Manager source: indeed.com

Salary in NYC

$121,000 / year

Product managers guide product development from ideation to market. Starting with consumer and market research, they use their understanding of customer wants and needs to inform product development and go-to-market strategy. They will work closely with engineering, marketing, sales, and other teams to launch products. After launch, they solicit and analyze feedback on the product to inform future iterations.

Interactive Training

Learn in Real-Time with Small Class Sizes

Attend courses in-person in NYC or Live Online via Zoom. Engage with expert instructors, ask questions, and get feedback on your exercises and projects. Switch between live-online and in-person as needed, even after the course has started.

Unlike other providers, these are not mass open-enrollment classes. At Noble Desktop, you’ll learn in small groups (typically 8-15 students) and receive personalized attention.

On Campus in NYC 185 Madison Ave, NYC

Get face-to-face interaction with an instructor and other students when you learn at our NYC campus. Courses are hands-on with a computer and software provided.

Live, interactive class
Experienced instructor in the room with you
Computer and software provided

More about our campus

Live Online Remote, from anywhere

Get the same interactivity and access to the instructor as in-person students. There are no extra fees and we’ll work with you to ensure your remote setup is perfect.

Live, interactive class
Experienced instructor teaching over Zoom
Remote setup assistance provided

More about live online training

photo of instructor leading a class in person

student taking a class live online, seated on their living room floor, leaning against a couch

Upcoming Python Classes in NYC or Live Online

All times are listed in Eastern Time unless otherwise specified.

September 2023
Python for Data Science Bootcamp September 23–October 21 Saturdays 10–5pm	$1,495 30 Hours NYC or Live Online	Unlock the power of Python for data-driven decision-making as you master Python programming fundamentals and dive into data analysis. Acquire essential skills to clean and manipulate data, create insightful visualizations, and perform statistical analysis, all through hands-on projects with real-world datasets.
Data Science Certificate September 23–February 17 Saturdays 10–5pm	$3,995 114 Hours NYC or Live Online	Learn Python, SQL, automation, and machine learning to become a Data Scientist. Gain Python programming, data analysis, SQL querying, and predictive modeling skills. Perfect for beginners, this program prepares you for entry-level data science and Python engineering roles. Unlock high-paying job opportunities in the field of data science.
FinTech Bootcamp September 23–February 17 Saturdays 10–5pm	$4,995 114 Hours NYC or Live Online	Get the skills you need for a career in finance technology with the FinTech Bootcamp. Learn Python programming, data science, financial analysis, data visualization, and machine learning to become a Financial Analyst, Data Scientist, or Data Analyst.
October 2023
Python Machine Learning Bootcamp October 10–16 Tuesday to Monday 10–5pm	$1,895 30 Hours NYC or Live Online	Learn the fundamentals of machine learning, including regression analysis and classification algorithms, in this practical, hands-on course. Gain the skills needed to solve real-world problems using machine learning, with a focus on Python programming and data science libraries.
Software Engineering Certificate October 10–March 12 Weekdays 10–5pm	$10,995 510 Hours NYC or Live Online	Learn front end development with HTML & CSS, JavaScript, and React, and back end development with Python, Django, and Node.js. Get 1-on-1 mentoring and a structured curriculum to become a skilled Software Engineer or Full Stack Developer.

showing 5 of 22 courses

Featured Python Bootcamps

Data Science Certificate

Python Developer Certificate

Python for Data Science Bootcamp

FinTech Bootcamp

Python Machine Learning Bootcamp

Python Data Science & Machine Learning Bootcamp

Learn the Most Powerful Programming Language

Learn Real-World Design & Coding Skills

30 Years of Experience