FinTech Bootcamp
Learn Python for financial analysis, machine learning, and algorithmic trading from experienced finance & engineering professionals in this 60-hour immersive.
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102 Hours
NYC or Live Online
We are open! Classes are running in-person (socially distanced) and live online. Secure your seat today
Learn Python for financial analysis, machine learning, and algorithmic trading from experienced finance & engineering professionals in this 60-hour immersive.
Jul 11–Aug 10
Weekdays
102 Hours
NYC or Live Online
In this certificate, students will learn how to use Python to pull, clean, analyze, visualize, and eventually predict off financial data. This program prepares students for entry-level positions in data science and financial technology as well as upskills any financial analyst.
Learn Python with an emphasis on data extraction, analysis, and visualization. Master the intricacies of the Python language, including a deep understanding of Python libraries of NumPy, Pandas, Matplotlib.
Learn how to apply advanced statistical concepts such as regression to build a predictive returns model on real-world financial data. Understand pivotal financial ratios and apply machine learning techniques to build valuation models.
Learn how to search through data using SQL. Master techniques to convert between data types, build tables, combine data, and create stored processes.
Want to discuss this class further? Email the program director hello@nobledesktop.com directly and find out if this is the right program for you.
Upon completion of this course, you’ll receive an official certificate testifying to your mastery of the curriculum. We’ll send you a link where you can download your certificate, share it online with your friends, post it to your professional network on LinkedIn, and view all your earned certificates. Congratulations on your achievement!
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Learn the concepts and skills covered in this program or your tuition is on us. See details and terms & conditions.
Work on projects proven to boost retention
Refined over many cohorts for an optimal learning experience
I didn't expect to learn much in a 4 session Python course, but Art's teaching style was very fitting for me. As the Chinese proverb states: Tell me, I'll forget. Show me, I'll remember. Involve me, I'll understand.
—James C.
Experienced educators who are driven to help you succeed
Refresh the materials and gain additional practice
We want you to succeed in your career goals. In addition to 102 hours of hands-on, interactive training, you’ll also receive four 1-on-1 mentoring sessions where you can:
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.
Course times are listed in Eastern Time.
Jul 11–15 | Mon–Fri | 10am–5pm | Python for Data Science Immersive |
Jul 18–20 | Mon–Wed | 10am–5pm | SQL Bootcamp |
Jul 22 | Friday | 10am–5pm | Python for Automation |
Jul 25–29 | Mon–Fri | 10am–5pm | Python Machine Learning Immersive |
Aug 8–10 | Mon–Wed | 10am–5pm | Python for Finance Immersive |
Jul 11–Aug 10 | Mon & Wed | 6–9pm | Python for Data Science Immersive |
Aug 15–31 | Mon & Wed | 6–9pm | SQL Bootcamp |
Sep 12 & 14 | Mon & Wed | 6–9pm | Python for Automation |
Sep 19–Oct 26
Except: Sep 26, Oct 5 |
Mon & Wed | 6–9pm | Python Machine Learning Immersive |
Oct 31–Nov 16 | Mon & Wed | 6–9pm | Python for Finance Immersive |
Oct 31–Nov 4 | Mon–Fri | 10am–5pm | Python for Data Science Immersive |
Nov 7–9 | Mon–Wed | 10am–5pm | SQL Bootcamp |
Nov 10 | Thursday | 10am–5pm | Python for Automation |
Nov 14–18 | Mon–Fri | 10am–5pm | Python Machine Learning Immersive |
Nov 28–30 | Mon–Wed | 10am–5pm | Python for Finance Immersive |
Jul 11–15 | Mon–Fri | 10am–5pm | Python for Data Science Immersive |
Jul 18–20 | Mon–Wed | 10am–5pm | SQL Bootcamp |
Jul 22 | Friday | 10am–5pm | Python for Automation |
Jul 25–29 | Mon–Fri | 10am–5pm | Python Machine Learning Immersive |
Aug 8–10 | Mon–Wed | 10am–5pm | Python for Finance Immersive |
Oct 31–Nov 4 | Mon–Fri | 10am–5pm | Python for Data Science Immersive |
Nov 7–9 | Mon–Wed | 10am–5pm | SQL Bootcamp |
Nov 10 | Thursday | 10am–5pm | Python for Automation |
Nov 14–18 | Mon–Fri | 10am–5pm | Python Machine Learning Immersive |
Nov 28–30 | Mon–Wed | 10am–5pm | Python for Finance Immersive |
Jul 11–Aug 10 | Mon & Wed | 6–9pm | Python for Data Science Immersive |
Aug 15–31 | Mon & Wed | 6–9pm | SQL Bootcamp |
Sep 12 & 14 | Mon & Wed | 6–9pm | Python for Automation |
Sep 19–Oct 26
Except: Sep 26, Oct 5 |
Mon & Wed | 6–9pm | Python Machine Learning Immersive |
Oct 31–Nov 16 | Mon & Wed | 6–9pm | Python for Finance Immersive |
Need more flexibility? Tap the button below to individually choose class date options for each class in this program.
If you prefer to pay your tuition over time, we have payment options to meet your needs. Finance your education through an installment plan or a 0% interest student loan. We also assist with documentation should your employer offer tuition reimbursement.
Each installment is charged to your card on file one week before the start of the associated course. The payment schedule may vary if the courses are taken in a different order
Installments | List Price | |
---|---|---|
$449.50 | 10% non-refundable deposit | -- |
$1,495.00 | Python for Data Science Immersive | $1,495 |
$975.00 | SQL Bootcamp | $975 |
$425.00 | Python for Automation | $425 |
$1,150.50 | Python Machine Learning Immersive | $1,895 |
▴ Your 10% deposit has been applied, as well as the certificate discount of $1,590 | ||
Free | Python for Finance Immersive | $1,295 |
$4,495.00 | Total You Pay |
See the Installment plan FAQ for more information.
See the Installment plan FAQ for more information.
Student loan provided through Climb Credit. See the Climb Credit FAQ for more information.
If you’re a company enrolling your employees, choose Corporate Invoice at checkout.
If you’re an employee seeking to have your tuition reimbursed by your company, email us for an invoice to submit to your employer for approval.
There are no extra fees or taxes for our courses. The price you see on this page is the maximum you’ll pay us.
However, if you plan to take the course live online, you may need to obtain required software. We’ll help you get set up with a free trial of paid software prior to the class. Most of our coding classes utilize freely-available open-source software. For most of our design and motion graphics courses, we will help you get set up with a free trial of Adobe Creative Cloud. If you attend the course in-person, we will have a computer already set up for you with all of the required software for no additional cost.
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.
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.
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.
This is the recommended order, but some courses may be taken in a different order. See the FAQ for more details.
Unit 1 30 Hours
Programming foundations including objects, loops, and functions
The object-oriented programming paradigm
How to work with different types of data such as strings, lists, and integers
Selectively alter the control flow of your programming with conditional statements
Analyze tabular data using Python libraries NumPy and Pandas
Create data visualizations with Matplotlib
Predict outcomes using linear regression with Scikit-Learn
Unit 2 30 Hours
Unit 3 18 Hours
Unit 4 6 Hours
Unit 5 18 Hours
In this advanced course, you will cover the major Python financial libraries to gather and manipulate financial data. You will start by working with financial APIs to fetch financial, company, and economic data. We will analyze financial statements from the SEC website, including financial ratios derived from the income statement and balance sheet. You will build a risk management models using Python libraries to create VAR models and Monte Carlo simulation. We will learn how to apply statistical measures such as linear regression to financial uses such as stock prices.
In addition to 102 hours of interactive training, you will receive four 1-on-1 mentoring sessions that can be used for career and job support, including polishing your resume, preparing for interviews, and reviewing best practices for applying to jobs. Note, however, that we don’t provide job placement (i.e. reaching out to companies on your behalf).
Students without any background in corporate finance or financial accounting should review our free online prep materials before the course (request the free materials after registration).
Typical class size ranges from 8–12 students, but we accept up to 20 students.
Students must be comfortable using a computer. No other prior knowledge is required.
Yes, this course is eligible for our installment plan or a 12-month financing plan through Climb Credit (no interest or fees).
Learn more in the Financing section above.
You may attend this training virtually (online) at the scheduled time the course is offered (New York, Eastern Time).
Select up to two courses and tap Compare selected courses to view a side-by-side comparison of FinTech Bootcamp with your selected courses.
This course will begin with advanced Python and statistic topics such as object-orientated programming and regression models. Students will learn how to apply these concepts using real-world financial data by building a predictive returns model using regression. We will then introduce students to important financial statements and ratios, and how to pull data from these statements and compute these important financial ratios using Python.
Master the tools to become a data scientist: Python, SQL, automation, and machine learning. Learn Python programming fundamentals and analyze data with Pandas, NumPy, and Matplotlib, and query databases with SQL. Use machine learning to apply regressions and other statistical analysis to create predictive models.
In this advanced course, you will cover the major Python financial libraries to gather and manipulate financial data. You will start by working with financial APIs to fetch financial, company, and economic data. We will analyze financial statements from the SEC website, including financial ratios derived from the income statement and balance sheet. You will build a risk management models using Python libraries to create VAR models and Monte Carlo simulation. We will learn how to apply statistical measures such as linear regression to financial uses such as stock prices.
Purchase group class vouchers at a discount for our regularly-scheduled group classes in NYC, or create a custom training program at your offices.
We’ve trained thousands of companies!
Let us create the perfect program for your team.