Python Learning Roadmap: From Foundations to Advanced Specializations

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Foundations

  • Install Python and set up an IDE (PyCharm, VSCode).
  • Learn syntax, data types, operators, control flow, and functions.

You Should Know:

 Check Python version 
python --version

Install virtual environment 
python -m venv myenv

Activate environment (Linux/macOS) 
source myenv/bin/activate

Install packages 
pip install numpy pandas 

Data Structures & Algorithms

  • Master lists, tuples, sets, dictionaries.
  • Learn stacks, queues, trees, and sorting algorithms.

You Should Know:

 Example: Quick Sort in Python 
def quicksort(arr): 
if len(arr) <= 1: 
return arr 
pivot = arr[len(arr) // 2] 
left = [x for x in arr if x < pivot] 
middle = [x for x in arr if x == pivot] 
right = [x for x in arr if x > pivot] 
return quicksort(left) + middle + quicksort(right) 

OOP & Advanced Concepts

  • Classes, inheritance, polymorphism, decorators.
  • Functional programming, error handling, file I/O.

You Should Know:

 Class example 
class Car: 
def <strong>init</strong>(self, brand, model): 
self.brand = brand 
self.model = model

def display(self): 
print(f"{self.brand} {self.model}") 

Web Development & Data Science

  • Flask/Django, REST APIs, NumPy, Pandas, TensorFlow.

You Should Know:

 Run Flask app 
export FLASK_APP=app.py 
flask run

Install ML libraries 
pip install scikit-learn tensorflow 

DevOps & Deployment

  • Git, Docker, CI/CD with GitHub Actions.

You Should Know:

 Git commands 
git init 
git add . 
git commit -m "Initial commit"

Dockerize Python app 
docker build -t my-python-app . 
docker run -p 4000:80 my-python-app 

Best Practices

  • PEP 8 compliance, security hardening, performance optimization.

You Should Know:

 Check PEP 8 compliance 
pip install pycodestyle 
pycodestyle script.py

Secure pip installations 
pip install --user --require-hashes -r requirements.txt 

What Undercode Say

Mastering Python requires structured learning and hands-on practice. Focus on real-world projects, contribute to open-source, and stay updated with AI/ML advancements. Use Linux for development to leverage powerful scripting (grep, awk, sed) and automation (cron, bash).

Expected Output:

A skilled Python developer capable of building scalable applications, automating workflows, and implementing machine learning solutions.

Prediction

Python will remain dominant in AI/ML, with increased integration in cybersecurity (e.g., penetration testing with scapy, automation with paramiko). Upskill in PyTorch and Kubernetes for future-proofing.

Relevant URLs:

IT/Security Reporter URL:

Reported By: Habib Shaikh – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅

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