🧮 Essential for ML pipelines and performance.

🧠 Module 5: Machine Learning (Supervised & Unsupervised)

Supervised Models:

• Linear & Logistic Regression
• KNN, Decision Trees, Random Forest
• SVM and Naive Bayes

Unsupervised Models:

• K-Means, Hierarchical Clustering
• DBSCAN, PCA

Hands-On:

• Model evaluation: accuracy, precision, recall, F1
• Confusion matrices, ROC curves
• Sklearn pipelines & hyperparameter tuning

📊 From theory to full model training and testing.

🧬 Module 6: Deep Learning with TensorFlow/Keras

Projects Built:

• CNN for image classification (Fashion MNIST)
• LSTM/RNN for sentiment analysis (IMDb)
• GAN for digit generation (MNIST)

Concepts Learned:

• Activation functions, optimizers
• Dropout, batch normalization
• Model training, validation, and evaluation

⚙️ End-to-end deep learning mastery.

🦜 Module 7: LangChain for LLM Apps

Skills Practiced:

• Using chat models via OpenAI or Groq
• Designing prompt templates
• Creating multi-step chains
• Building RAG (Retrieval-Augmented Generation) apps
• Implementing LLM Agents with memory and tools

🧠 LLM orchestration like a pro.

🧾 Module 8: Prompt Engineering

Learned Techniques:

• Zero-shot, one-shot, few-shot prompts
• Role prompting & instruction tuning
• Prompt templates for classification, reasoning, coding, Q&A
• Prompt testing for performance & consistency

💡 Crafting the perfect instructions for GenAI models.

🤗 Module 9: Hugging Face Transformers

Hands-On With:

• transformers and pipeline() API
• Text classification, translation, summarization
• Tokenizers and model configuration
• Model comparisons and use-case matching

🤖 Using state-of-the-art models in minutes.

🧠 Module 10: Classical NLP Techniques

Explored Concepts:

• Tokenization, stemming, lemmatization
• Stopword removal, POS tagging, NER
• TF-IDF, Bag-of-Words
• Built a mini NLP pipeline using NLTK and Scikit-learn

📚 Before transformers, came the classics.

🎨 Module 11: Generative AI with Gradio & Streamlit

Hands-On Projects:

• Build Text-to-Image Generator with Stable Diffusion
• Deploy custom models using Gradio UI
• Build AI dashboards with Streamlit

Skills Gained:

• Hosting ML models in the browser
• Interactive AI app design
• Sharing and deploying apps on Hugging Face Spaces

🌐 From local models → to user-friendly AI apps.

🤖 Module 12: Agentic AI

Submodules & Practice Areas:

• 01_N8N Automation Agents

  • No-code workflows for AI agents
  • Connecting APIs and automation flows

• 02_Agents with LangChain

  • Building task-specific AI agents
  • RAG-based agents for knowledge retrieval
  • Tool-using agents with memory

• 03_Multiple Agents with CrewAI

  • Multi-agent collaboration frameworks
  • Role assignment and task orchestration
  • Real-world simulations with CrewAI

🕹️ From single-task bots → to autonomous, multi-agent systems.

🧰 Tools & Frameworks

Built as part of the iCodeGuru Python & AI Bootcamp

“Learn by building. Master by sharing.”
Designed for developers, data enthusiasts, and aspiring AI engineers.

⭐ Star this Repo if You Learned Something!

Share your progress, collaborate, and contribute to the AI community.
Happy Learning 🚀

This repository contains jupyter notebooks and python files used while studying agentic AI and LLMs