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Jenni Juli
Jenni Juli

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Python AI Roadmap (Beginner Expert)

**1. Python Basics
**Goal: Build a strong foundation in Python

Learn:

  • Python syntax, variables, data types
  • Control statements (if, for, while)
  • Functions, modules, error handling
  • Object-Oriented Programming (OOP) basics
  • Tools/Libraries: Jupyter Notebook, VS Code
  • Mini Projects: Calculator, To-Do App, Number Guessing Game

2. Data Handling & Analysis
Goal: Learn to work with data (the core of AI)

Learn:

  • NumPy (arrays, vectors, matrices)
  • Pandas (data cleaning, manipulation)
  • Matplotlib & Seaborn (data visualization)
    Mini Projects:

  • Sales data analysis

  • COVID-19 data visualization

  • Weather data trends

3. Machine Learning Fundamentals

Goal: Understand ML concepts & algorithms

Learn:

  • Scikit-learn (classification, regression, clustering)
  • Supervised vs Unsupervised learning
  • Feature scaling, model evaluation, cross-validation
  • Linear Regression, Logistic Regression, Decision Trees, KNN, Random Forests
    **
    Mini Projects:**

  • Spam email classifier

  • Predict house prices

  • Customer segmentation

4. Deep Learning & Neural Networks
Goal: Learn how neural networks power AI

Learn:

  • TensorFlow & PyTorch basics
  • Artificial Neural Networks (ANNs)
  • Convolutional Neural Networks (CNNs) – Image recognition
  • Recurrent Neural Networks (RNNs), LSTMs – Time-series & text

Mini Projects:

  • Handwritten digit recognition (MNIST)
  • Sentiment analysis on tweets
  • Stock price prediction

5. Advanced AI Topics (12–20 weeks)

Goal: Move from ML/DL → AI systems

Learn:

  • Natural Language Processing (NLP) with Hugging Face, spaCy
  • Reinforcement Learning basics (OpenAI Gym)
  • Generative AI (GANs, diffusion models, transformers)
  • Large Language Models (LLMs) with LangChain, Hugging Face

Mini Projects:

  • Chatbot using Transformers
  • Text summarizer or Q&A bot
  • AI image generator

**6. AI Projects & Deployment (Ongoing)
**Goal: Build real-world AI apps

Skills:

  • Flask/FastAPI for AI model deployment
  • Streamlit/Gradio for AI app UI
  • Cloud & MLOps basics (AWS, Azure, Docker, GitHub Actions)

Projects:

  • AI-powered recommendation system
  • Voice assistant
  • Real-time object detection app
  • AI SaaS product (end-to-end project)

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