Last Updated on July 22, 2025
Your Journey from Zero to Agentic AI
By Pranu Kumar – Senior Software Developer & Digital Government Specialist
🚀 Overview
Welcome to the AI Engineering Tracks curated by Pranu Kumar, designed to take developers, architects, and digital transformation professionals from foundational AI skills to building enterprise-grade, agentic, and sector-specific AI solutions.
This track is split into two clear paths:
- 🔹 General AI (Zero to Agentic AI) – For building intelligent apps, LLM agents, and ML-powered systems.
- 🔸 AI for Government & Sectors – For applying AI in domains like Railways, Health, AgriTech, Education, and Smart Cities.
Both tracks are broad, production-ready, and aligned with real-world problems and emerging AI-first architectures.
🔹 General AI Engineering Track (Zero to Agentic AI)
Goal: Equip developers and architects to build ML/LLM-based solutions, agents, and autonomous systems.
📦 Modules:
🌱 Foundations & ML Basics
- Python for ML (NumPy, Pandas, Matplotlib)
- Classical ML with Scikit-learn (Regression, Clustering, Trees)
- Intro to Deep Learning: ANN, CNN, RNN
💬 GenAI & LLM Integration
- Prompt Engineering (ChatGPT, Claude, Gemini)
- LangChain, LlamaIndex & RAG Patterns
- LLM App Patterns: Chatbots, Semantic Search, Auto-fill
👁️ Computer Vision
- Image classification, object detection
- Document parsing with OCR (Tesseract + OpenCV)
- AI for invoice, ID card, and form recognition
🧠 Agentic AI & Multi-Agent Systems
- ReAct, AutoGPT, BabyAGI, CrewAI
- Multi-tool, multi-agent orchestration
- Agents with memory, function calling & tool use
⚙️ MLOps & Lifecycle
- MLflow, DVC, CI/CD for ML
- Model Monitoring, Drift Detection
- Deployment to cloud, edge & Kubernetes
🔐 Responsible & Secure AI
- Bias & fairness in ML models
- LLM security (Prompt injection, adversarial prompts)
- Data privacy & compliance (GDPR, DPDP)
🔸 AI for Government & Sector-Specific Missions (AI for Bharat)
Goal: Use AI to transform citizen services, governance workflows, and sectoral missions at scale.
🏛️ Domains Covered:
🚆 Railways & Transport
- Predictive maintenance (sensor + ML)
- NLP for circulars, rules, inspection docs
- CV for wagon/track inspection
- GenAI assistant for HQ & Zonal officers
📈 Agriculture & Rural
- Satellite + ML crop prediction
- Pest detection with image models
- Agri-Advisory chatbot in regional languages
🏥 HealthTech & Public Health
- Health records digitization (OCR + NLP)
- Disease surveillance models
- Clinical chat assistant for ANMs/doctors
🏫 Education & Skilling
- AI for grading & feedback
- Personalized learning engine
- Dropout prediction models
🏙️ Urban Local Bodies
- Complaint classification & routing
- Smart city sensor data predictions
- Building Plan Approval with AI validation
📑 Governance & Public Services
- Circular & policy summarizer bots
- Digilocker + GenAI document explanations
- Grievance escalator bots + escalation agents
📦 Procurement & QA
- Tender risk scoring & summary agents
- Vendor inspection via CV + RPA
- Contract compliance bots (NLP + rules)
🪙 Audit, Revenue, Legal
- Audit draft generator (GenAI + reports)
- Anomaly detection in tax systems
- Legal Q&A + Section Explainer bots
🎯 Who Should Follow This Track?
- Full-Stack Java Developers entering ML/AI
- Enterprise Architects driving AI adoption
- Govt. IT Professionals building e-governance systems
- AI Enthusiasts exploring Agent-based systems
🔗 What You’ll Get:
- ✅ Tutorials & Use Cases
- ✅ Code samples and walkthroughs
- ✅ Architecture Blueprints
- ✅ Sector-specific PoC ideas
- ✅ GitHub & Deployment-ready projects
🔍 Start Learning →
Explore tutorials from both tracks under the Tutorials section or browse through featured blog posts on AI & digital transformation.
Pranu Kumar
Senior Software Developer @CIPL (CRIS Project)
AI for Bharat | Full-Stack Java | Microservices | Secure e-Gov Solutions
🌐 www.pranukumar.in