PythonForFinance

Repository to hold the PythonForFinance course for Audencia

Planning

Date	Time Slot	Validated
15/09	13h30 - 17h45	Introduction
22/09	13h30 - 17h45	Variable, loops, conditions
24/09	13h30 - 17h45	Fonctions, Classes, Scripts et API
06/10	13h30 - 17h45	Libraries, package manager, dataframe et data viz
08/10	13h30 - 17h45	Backend / Frontend integration
14/10	13h30 - 17h45	GenAI / LLMs for development

Course Content (previsionnal)

• Seance 1 : Introduction
  • Amphi
    • History of python
    • Examples of python projects in enterprise
    • Python project lifecycle and basics of agile development
    • Structure of a python project in enterprise
    • Using GIT (repo, push, pull, pull request etc.)
    • Python in 2025 (AI / Adoption / Challenges)
    • Presentation of the red thread project
    • Presentation of the evaluation project
  • TD
    • Installing python
    • Setting up an IDE (VS Code)
    • Setting up AI in the ide
    • First python program: Hello World
• Seance 2 : Python Basics
  • Amphi
    • Data types (int, float, string, bool)
    • Data structures (list, tuple, dict, set)
    • Operators (arithmetic, comparison, logical)
    • Conditions (if, elif, else)
    • Loops (for, while)
    • Basic algorithmic optimization (type simplification, complexity, stop conditions)
  • TD
    • Loading a tweet dataset json into a list of dictionaries
    • Defining an appropriate data model
    • Implementing a filter on the number of likes and the presence of verbatims
    • Extracting high-level KPIs (number of tweets, number of likes, number of retweets, number of followers, number of following)
• Seance 3 : Functions, Classes, Scripts and API
  • Amphi
    • Learning to define a function
    • Learning to define a pipeline
    • Learning to define a class
    • When to use a class, when to use a function
    • Basic notions of inheritance and design patterns
    • Learning to run a .py
    • Learning to use an API
  • TD
    • Creating a function to calculate the number of words in a text
    • Creating a function to remove stop words in a text
    • Creating a Tweet class to standardize tweet processing
    • Creating a cleaning and enrichment pipeline for tweets
    • Learning to query a simple API
• Seance 4 : Libraries, package manager, dataframe and data viz
  • Amphi
    • Understanding how a package manager works
    • Installing libraries
    • Browsing a documentation and being autonomous on a library
    • Introduction to Pandas
    • Introduction to Plotly
    • Learning to install a git library: https://github.com/JustAnotherArchivist/snscrape
  • TD
    • Installing pandas / plotly
    • Adapting previous functions to use a pandas dataframe
    • Creating data aggregation queries to extract KPIs
    • Visualizing results and trends with Plotly
    • Retrieving tweets with SNScrape
    • Simple sentiment analysis with text blob
    • Bonus: creating a wordcloud
• Seance 5 : Backend / Frontend
  • Amphi
    • What are the differences between back-end and front-end development
    • Creating a simple fastapi backend
    • Creating a simple client to query fastapi
    • Setting up a basic interface in gradio / streamlit
  • TD
    • Modularizing previous functions and serving them via a fastapi backend
    • Creating a simple interface to query the backend
    • Allowing data ingestion directly via the interface
• Seance 6 : GenAI / LLMs
  • Amphi
    • How generative AI integrates into python development
    • What is an "agent" and how to query it
  • TD
    • Adding a sentiment analysis / title / paraphrasing tool to tweets