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jpmorganchase/python-training

13,171Jupyter NotebookAudience · dataComplexity · 1/5LicenseSetup · easy

TLDR

JPMorgan Chase's Python training notebooks teaching numerical computing and data visualization to business analysts and traders, runnable in a browser with no local setup required.

Mindmap

mindmap
  root((repo))
    What it does
      Numerical computing
      Data visualization
      Financial examples
    Tech Stack
      Python
      Jupyter Notebooks
      Binder cloud runner
    Use Cases
      Learn Python basics
      Financial data work
      Team training sessions
    Audience
      Business analysts
      Traders
      Finance non-coders
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Things people build with this

USE CASE 1

Learn Python basics for numerical analysis and data visualization without installing anything, using only a web browser.

USE CASE 2

Follow JPMorgan's analyst training curriculum to build Python skills for working with financial data.

USE CASE 3

Adapt the notebooks for your own Python intro training sessions aimed at non-programmer colleagues.

Tech stack

PythonJupyter NotebookBinder

Getting it running

Difficulty · easy Time to first run · 5min

No local install needed, click the Binder link to open and run notebooks directly in your browser.

Apache 2 license, use freely for any purpose including commercial projects, as long as you include the original license and copyright notice.

In plain English

This repository contains Python training materials created by JPMorgan Chase for business analysts and traders inside the bank, as well as for select institutional clients. The materials are presented as Jupyter Notebooks, which are interactive documents that mix written explanation with runnable code, making them well-suited for learning by doing. The course is described as an introduction to numerical computing and data visualization in Python. It is not meant to be a full computer science curriculum. Instead, the goal is to show people without formal programming backgrounds that relatively complex analytical tasks can be done with relatively approachable code. Topics such as working with numbers and drawing charts from financial data fall within the scope of what the materials cover. The training is designed to be led in person by JPMorgan technologists and traders rather than as a fully self-guided resource. Institutional clients who are interested in access are directed to contact their JPMorgan team. The notebooks can be launched in a cloud environment directly from the repository without any local setup, using a service called Binder. This lets learners open the material in a browser and run code without installing anything on their own computer. Financial data used in the exercises comes from IEX Cloud, and geographic data (airports and routes) comes from OpenFlights.org. The code is released under the Apache 2 license. The repository has no stated prerequisites or syllabus in the README beyond the overview description, so the detailed lesson content lives inside the notebooks themselves rather than in this top-level file.

Copy-paste prompts

Prompt 1
I'm a business analyst new to Python. Walk me through plotting a chart of stock price data using the same approach as the JPMorgan python-training notebooks.
Prompt 2
Using the JPMorgan python-training style, show me how to load financial data from a CSV and calculate a 30-day moving average.
Prompt 3
Help me adapt one of the JPMorgan python-training exercises to use data from my own spreadsheet instead of IEX Cloud.
Prompt 4
Which Python concepts covered in the JPMorgan training notebooks are most important for someone who analyzes trading data daily?
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