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Training plan · Development · Beginner to Intermediate
Python Development
Intensive 3-day training to master Python: fundamentals, OOP, Pandas, web scraping, automation and final project.
Duration
3 jours (21h)
Format
On-site
Prerequisites
None (basic logic is enough)
Audience
Programming beginners, analysts, interns
1
Day 1 — Python: Fundamentals
1j- Python intro: installation, IDLE, VS Code, REPL, script execution
- Variables: types, assignment, dynamic typing
- Operators: arithmetic, comparison, logical, identity, membership
- Strings: concatenation, f-strings, slicing, methods
- Lists: creation, index, slicing, methods, list comprehension
- Dictionaries: creation, keys/values, methods
- Tuples and sets: immutability, set operations
- Conditions: if/elif/else, match/case (Python 3.10+)
- Loops: for, while, range, enumerate, break, continue, else
- Functions: def, return, parameters, args/kwargs, lambda, docstrings
- Intensive lab 1: create a contact management program (add, list, search, file save)
2
Day 1 — Files, Exceptions & Modules
- Text files: open, read, write, append, with, r/w/a modes
- CSV files: csv.reader, csv.writer, DictReader, DictWriter
- JSON files: json.load, json.dump, json.loads, json.dumps
- Exceptions: try/except/else/finally, exception types, raise
- Modules: import, from, as, __name__, __main__
- Standard modules: os, sys, datetime, random, math, statistics
- PIP: package installation, requirements.txt, virtual environments
- Intensive lab 2: create a CSV analysis script with statistics and JSON export
3
Day 2 — Object-Oriented Programming
1j- Classes and objects: class, __init__, self, attributes, methods
- Inheritance: super(), overridden methods, multiple inheritance
- Encapsulation: private attributes (__), properties (@property)
- Special methods: __str__, __repr__, __len__, __eq__
- Abstract classes: ABC, abstractmethod
- Decorators: @staticmethod, @classmethod, simple decorator
- Iterators and generators: __iter__, __next__, yield
- Intensive lab 3: create a LibraryManager class with books, members, loans and searches
4
Day 2 — Essential Libraries
- NumPy: arrays, shape, reshape, vector operations
- Pandas: Series, DataFrame, read_csv, head, info, describe, groupby
- Matplotlib: plot, scatter, bar, hist, title, legend, savefig
- Seaborn: countplot, heatmap, pairplot, boxplot, style
- Requests: GET, POST, JSON, headers, timeout, error handling
- BeautifulSoup: HTML parsing, find, select, tree navigation
- Intensive lab 4: analyze a sales CSV with Pandas, create charts and query an API
5
Day 3 — Automation & Useful Scripts
1j- File automation: os.walk, glob, shutil (copy, move, archive)
- Email: smtplib, email.mime, sending emails with attachments
- PDF: PyPDF2, text extraction, merge, rotate
- Excel: openpyxl, read/write, formatting, charts
- Web scraping: requests + BeautifulSoup, pagination, CSV export
- Network programming: socket, simple HTTP client
- Intensive lab 5: create a scraping + PDF report generation + email sending script
6
Day 3 — Final Project & Best Practices
- Project choice: data analysis, scraping, automation or console app
- Structure: modules, functions, classes, docstrings, typing
- Testing: unittest, pytest, assert, test coverage
- Documentation: docstrings, README, comments
- Git: versioning, commit, push, GitHub
- Project presentation: demo, code review
- Python assessment and certification
This plan is customizable
Perfect for programming beginners as well as analysts wanting to automate their tasks.