Detailed Syllabus & Weekly Breakdown

Semester 1: Fundamentals of AI & NLP Architectures (Weeks 1–12)

• Module 1: AI Foundations & Search Algorithms (Weeks 1–6)
  • Week 1-2: Intro to Artificial Intelligence vs Machine Learning vs Deep Learning
  • Week 3-4: Knowledge Representation & Search Strategies (A*, Heuristics)
  • Week 5-6: Foundations of Machine Learning Pipelines (Data to Deployment)
• Module 2: Natural Language Processing (NLP) Fundamentals (Weeks 7–12)
  • Week 7-8: Text Preprocessing, Tokenization, and TF-IDF
  • Week 9-10: Word Embeddings (Word2Vec) and Sequence Models (RNN/LSTM)
  • Week 11-12: Sentiment Analysis & Named Entity Recognition (NER)

Semester 2: Deep Learning & Generative AI (Weeks 13–24)

• Module 3: Deep Learning & Transformers (Weeks 13–18)
  • Week 13-14: Intro to PyTorch/TensorFlow for Neural Networks
  • Week 15-16: The Attention Mechanism & Transformer Architectures
  • Week 17-18: Pre-trained Models (BERT, T5, RoBERTa)
• Module 4: Generative AI & Large Language Models (LLMs) (Weeks 19–24)
  • Week 19-20: Prompt Engineering & Context Windows
  • Week 21-22: OpenAI APIs, Anthropic, & Open Source LLMs (HuggingFace)
  • Week 23-24: Fine-tuning LLMs (PEFT, LoRA) & Evaluation metrics

Semester 3: Agentic AI, RAG & Capstone (Weeks 25–36)

• Module 5: Building AI Agents (LangChain & RAG) (Weeks 25–30)
  • Week 25-26: Vector Databases (Pinecone, ChromaDB) & Embeddings
  • Week 27-28: Retrieval-Augmented Generation (RAG) Architecture
  • Week 29-30: Autonomous Agents, LangChain, & LlamaIndex
• Module 6: Enterprise Capstone (Weeks 31–36)
  • Week 31-32: System Design & Architecture Planning for AI Systems
  • Week 33-34: Core Development & Tool Integration
  • Week 35-36: UI Integration, Deployment & Final Viva

Learning Outcomes

• Architect and integrate intelligent NLP algorithms into modern web platforms.
• Deploy robust Deep Learning models scaling via PyTorch and TensorFlow framework.
• Design sophisticated Generative AI and LLM solutions using cutting-edge APIs.
• Develop autonomous agent systems utilizing RAG architectures and LangChain.

Assessment Weightage

Assessment Type	Weightage
Master Capstone Project & Live Deployment	30%
Hands-on Labs & Mini-Projects	30%
Module & Mid-Term Assessments	20%
Final Viva & Architecture Review	20%

The "WhiteCollar" Academic Rationale

This 9-month program trains you to lead the AI revolution. By progressively mastering Machine Learning fundamentals → NLP architectures → LLM Integrations → Autonomous Agents, WhiteCollar Academy ensures that graduates are not just consuming AI services, but building robust, secure, and highly scalable AI products ready for the enterprise environment.