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Course Details
Price:
$4,995 30 seats left
Start Date:

Mon, Jun 12, 10:00am - Jul 11, 5:00pm Eastern Time ( 19 sessions )

Next start dates (4)

Location:
Midtown, Manhattan
185 Madison Ave 3rd Fl
Btwn E 34th & E 35th Streets
New York, New York 10016
(Map)
Important:
No class on June 19, July 3 and July 4
Purchase Options
Description
Class Level: All levels
Age Requirements: 18 and older
Average Class Size: 25

What you'll learn in this coding class:

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. 

Master Advanced Python to Analyze Financial Data 
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. 

Use Machine Learning to Build Financial Models
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.

Algorithmic Trading using Python 
Learn how to build robust and automated trading strategies without needing to spend hours a day overseeing their portfolio. Master trading strategies such as exponential moving average (EMA), Moving Average Convergence Divergence (MACD), and backtesting. 

What You’ll Learn

  • Python: Handling different types of data, such as integers, floats, and strings
  • Python: Analyze tabular data with Numpy and Pandas and graph the results using Matplotlib
  • Python: Learn how to pull data from multiple sources 
  • Machine Learning: Learn how to analyze a financial statement  using Python 
  • Machine Learning: Learn financial topics such as WACC, NPV, IRR
  • Machine Learning: Learn how to build predictive models for internal budgeting 
  • Algorithmic Trading: Learn how to use Pyhton to automate trading 
  • Algorithmic Trading: Learn commonly used trading strategies 

Courses in the Certificate Program

This is the recommended order, but some courses may be taken in a different order

Python for Finance Immersive

Upskill and take your finance skills to the next level with this Python for Finance class. You'll learn to analyze large amounts of financial data using Python, create visualizations, and start using statistics for predictive modeling. 

Machine Learning & Automation for Finance

This course will begin with advanced Python and statistic topics such as object-orientated programming and regression models. After learning this first module, students will learn how to apply these concepts using real-world financial data by building a predictive returns model using regression.

The next section of the course will introduce students to important financial statements and ratios. After students learn these financial concepts, they will be introduced on how to pull data from these statements and compute these important financial ratios using Python

Algorithmic Trading with Python

As people get busier and busier, we want to automate as much as we can day to day including our investments. Using Python, this class will teach you how to build robust and automated trading strategies without needing to spend hours a day overseeing their portfolio. Students learn how to connect their Python scripts with an online trading brokerage, how to place and query stock orders, and are introduced to Machine learning as it applies to properly value an Option.


Learn more about FinTech Bootcamp at Practical Programming.


Still have questions? Ask the community.

Refund Policy

To reschedule or cancel, email us at [email protected]

All courses include a non-refundable registration fee (10% of the undiscounted course price).

  • Students may cancel up to 11 business days before the class/program start date and receive a refund, less the registration fee.
  • Cancellations within 11 business days are not permitted; however, students may reschedule up to 4 business days before the class start date.

Note: Any refunds must be requested within 180 days from the original payment date; courses rescheduled within 11 business days of the start date are not eligible for refunds.

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Practical Programming

All classes at this location

We are located in New York City on 34th street and Madison Avenue, a few blocks from Penn Station, Port Authority and Times Square. You may also attend this class live online (virtual training) via Zoom. We will reach out with additional information, including the Zoom info and class files.

Also available virtually online

Start Dates (5)
TBD
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Show all 19 sessions
  • Mon, Jun 12 at 10:00am - 5:00pm
  • Tue, Jun 13 at 10:00am - 5:00pm
  • Wed, Jun 14 at 10:00am - 5:00pm
  • Thu, Jun 15 at 10:00am - 5:00pm
  • Fri, Jun 16 at 10:00am - 5:00pm
  • Tue, Jun 20 at 10:00am - 5:00pm
  • Wed, Jun 21 at 10:00am - 5:00pm
  • Thu, Jun 22 at 10:00am - 5:00pm
  • Fri, Jun 23 at 10:00am - 5:00pm
  • Mon, Jun 26 at 10:00am - 5:00pm
  • Tue, Jun 27 at 10:00am - 5:00pm
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  • Fri, Jun 30 at 10:00am - 5:00pm
  • Wed, Jul 05 at 10:00am - 5:00pm
  • Thu, Jul 06 at 10:00am - 5:00pm
  • Fri, Jul 07 at 10:00am - 5:00pm
  • Mon, Jul 10 at 10:00am - 5:00pm
  • Tue, Jul 11 at 10:00am - 5:00pm
TBD
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  • Mon, Jul 17 at 10:00am - 5:00pm
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  • Wed, Jul 19 at 10:00am - 5:00pm
  • Thu, Jul 20 at 10:00am - 5:00pm
  • Fri, Jul 21 at 10:00am - 5:00pm
  • Mon, Jul 24 at 10:00am - 5:00pm
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  • Mon, Jul 31 at 10:00am - 5:00pm
  • Tue, Aug 01 at 10:00am - 5:00pm
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  • Mon, Aug 07 at 10:00am - 5:00pm
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  • Fri, Aug 11 at 10:00am - 5:00pm
  • Mon, Aug 14 at 10:00am - 5:00pm
  • Tue, Aug 15 at 10:00am - 5:00pm
TBD
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  • Mon, Aug 07 at 6:00pm - 9:00pm
  • Wed, Aug 09 at 6:00pm - 9:00pm
  • Mon, Aug 14 at 6:00pm - 9:00pm
  • Wed, Aug 16 at 6:00pm - 9:00pm
  • Mon, Aug 21 at 6:00pm - 9:00pm
  • Wed, Aug 23 at 6:00pm - 9:00pm
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  • Mon, Sep 04 at 6:00pm - 9:00pm
  • Wed, Sep 06 at 6:00pm - 9:00pm
  • Mon, Sep 11 at 6:00pm - 9:00pm
  • Wed, Sep 13 at 6:00pm - 9:00pm
  • Mon, Sep 18 at 6:00pm - 9:00pm
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  • Wed, Oct 25 at 6:00pm - 9:00pm
  • Mon, Oct 30 at 6:00pm - 9:00pm
  • Wed, Nov 01 at 6:00pm - 9:00pm
  • Mon, Nov 06 at 6:00pm - 9:00pm
  • Wed, Nov 08 at 6:00pm - 9:00pm
  • Mon, Nov 13 at 6:00pm - 9:00pm
  • Wed, Nov 15 at 6:00pm - 9:00pm
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  • Wed, Nov 22 at 6:00pm - 9:00pm
  • Mon, Nov 27 at 6:00pm - 9:00pm
  • Wed, Nov 29 at 6:00pm - 9:00pm
  • Mon, Dec 04 at 6:00pm - 9:00pm
  • Wed, Dec 06 at 6:00pm - 9:00pm
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  • Wed, Dec 20 at 6:00pm - 9:00pm
  • Mon, Dec 25 at 6:00pm - 9:00pm
  • Wed, Dec 27 at 6:00pm - 9:00pm
TBD
$4,995
Book
Show all 19 sessions
  • Mon, Sep 18 at 10:00am - 5:00pm
  • Tue, Sep 19 at 10:00am - 5:00pm
  • Wed, Sep 20 at 10:00am - 5:00pm
  • Thu, Sep 21 at 10:00am - 5:00pm
  • Fri, Sep 22 at 10:00am - 5:00pm
  • Tue, Sep 26 at 10:00am - 5:00pm
  • Wed, Sep 27 at 10:00am - 5:00pm
  • Thu, Sep 28 at 10:00am - 5:00pm
  • Fri, Sep 29 at 10:00am - 5:00pm
  • Mon, Oct 02 at 10:00am - 5:00pm
  • Tue, Oct 03 at 10:00am - 5:00pm
  • Wed, Oct 04 at 10:00am - 5:00pm
  • Thu, Oct 05 at 10:00am - 5:00pm
  • Fri, Oct 06 at 10:00am - 5:00pm
  • Tue, Oct 10 at 10:00am - 5:00pm
  • Wed, Oct 11 at 10:00am - 5:00pm
  • Thu, Oct 12 at 10:00am - 5:00pm
  • Fri, Oct 13 at 10:00am - 5:00pm
  • Mon, Oct 16 at 10:00am - 5:00pm
TBD
$4,995
Book
Show all 21 sessions
  • Sat, Sep 23 at 10:00am - 5:00pm
  • Sat, Sep 30 at 10:00am - 5:00pm
  • Sat, Oct 07 at 10:00am - 5:00pm
  • Sat, Oct 14 at 10:00am - 5:00pm
  • Sat, Oct 21 at 10:00am - 5:00pm
  • Sat, Oct 28 at 10:00am - 5:00pm
  • Sat, Nov 04 at 10:00am - 5:00pm
  • Sat, Nov 11 at 10:00am - 5:00pm
  • Sat, Nov 18 at 10:00am - 5:00pm
  • Sat, Dec 02 at 10:00am - 5:00pm
  • Sat, Dec 09 at 10:00am - 5:00pm
  • Sat, Dec 16 at 10:00am - 5:00pm
  • Sat, Dec 23 at 10:00am - 5:00pm
  • Sat, Dec 30 at 10:00am - 5:00pm
  • Sat, Jan 06 at 10:00am - 5:00pm
  • Sat, Jan 13 at 10:00am - 5:00pm
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  • Sat, Jan 27 at 10:00am - 5:00pm
  • Sat, Feb 03 at 10:00am - 5:00pm
  • Sat, Feb 10 at 10:00am - 5:00pm
  • Sat, Feb 17 at 10:00am - 5:00pm
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