VedaAI — A SKool of Artificial Intelligence

Course Catalogue

5 AI Programs for Every Level

Product-first, GenAI-first, Deployment-first. Every programme ends with a live deployed AI product — not just a certificate.

Program 01 / 05

AI Foundations & GenAI Mastery

Duration3 Months

LevelBeginner to Intermediate

Core SkillsPython · ML · Deep Learning · LLMs · Prompt Engineering · RAG · GenAI App Deployment

Tools & PlatformsTensorFlow · Keras · OpenAI API · ChromaDB · FAISS · No-Code Platform

Who is this for?College students, CS graduates, and developers who want a complete journey from Python basics to building and deploying GenAI-powered products.

Capstone Outcome: Design, build, and deploy a complete GenAI-powered SaaS web application using our No-Code platform — live on cloud, production-grade, and portfolio-ready for job applications.

Curriculum — Module by Module

Python & ML Foundations

Python for AI: OOP, NumPy, Pandas, Matplotlib. ML fundamentals: supervised/unsupervised learning, decision trees, regression, model evaluation, cross-validation, feature engineering. Build a real-world prediction model (house prices / student performance).

Neural Networks & Deep Learning

Perceptrons, activation functions, backpropagation, gradient descent. CNNs for image classification. TensorFlow/Keras fundamentals. Train, evaluate, and save models. Build an image classifier for real-world product recognition.

Large Language Models & Transformers

Transformer architecture, self-attention, positional encoding. GPT, BERT, LLaMA — architecture comparisons. Pre-training vs fine-tuning vs in-context learning. Tokenization, embeddings, vector representations. LLM limitations: hallucinations, bias, context windows.

Prompt Engineering & RAG

Zero-shot, few-shot, chain-of-thought, and tree-of-thought prompting. Prompt templates and structured outputs. OpenAI, Anthropic, Gemini API integration. RAG pipeline: vector databases (ChromaDB, FAISS), document ingestion, chunking, embedding, retrieval. Build a document Q&A chatbot over real data.

AI API Integration & Application Architecture

Connecting LLM APIs to web applications. Building chatbots, summarisers, and content generators. Understanding AI application architecture: frontend, backend, vector DB, and LLM layers. Error handling, rate limiting, and cost management for AI APIs.

GenAI App Capstone — No-Code Platform Deployment

Full GenAI product lifecycle: idea → architecture → build → deploy. Integrating LLMs into a complete web application using our No-Code platform. Cloud deployment walkthrough on AWS/GCP. Final capstone: a live, deployed GenAI-powered SaaS product presented to an industry panel.

Program 02 / 05

AI Agent Development

Duration4 Months

LevelIntermediate to Advanced

Core SkillsAI Agents · LangChain · LangGraph · AutoGen · CrewAI · Multi-Agent Systems · Production Deployment

Tools & PlatformsLangChain · LangGraph · AutoGen · Docker · AWS/GCP/Azure · Langfuse · LangSmith

Who is this for?Working professionals and developers who want to build autonomous AI agents and multi-agent enterprise automation systems.

Capstone Outcome: Design, build, and deploy a multi-agent business automation system on cloud — with real enterprise workflow integration, monitoring, and security guardrails in place.

Curriculum — Module by Module

Foundations of AI Agents

Agent vs chatbot vs assistant — architectural differences. ReAct (Reasoning + Acting) framework. Tool use and function calling in LLMs. Agent memory types: short-term, long-term, episodic, semantic. Task planning and decomposition with LLM reasoning. Build a simple ReAct agent that searches, reasons, and responds autonomously.

LangChain & LangGraph

LangChain agents: MRKL, OpenAI Functions, structured tools. LangGraph for stateful workflows: nodes, edges, state management. Custom tool creation: web search, database query, API call agents. Human-in-the-loop agent design. Build a research agent that retrieves, analyses, and reports on any topic.

Multi-Agent Systems

Multi-agent architectures: supervisor, collaborative, and debate models. AutoGen and CrewAI frameworks in depth. Agent communication protocols and message passing. Specialised agents: coding agent, data analyst, retrieval specialist. Failure handling, retry strategies, and fallback planning.

Agent Tools & Enterprise Integrations

REST and GraphQL API integration with agents. Browser automation using Playwright + AI. Database agents: SQL generation and schema understanding. Code execution agents. IoT data processing and action agents. Integration with CRM, ERP, and enterprise systems.

Agent Security, Guardrails & Observability

Prompt injection prevention and adversarial input handling. Output validation and content filtering. Agent tracing and debugging with Langfuse and LangSmith. Cost tracking and token budget management. GDPR and enterprise data compliance for agentic systems.

Production Deployment Capstone

Containerising agents with Docker. Cloud deployment on AWS/GCP/Azure. CI/CD pipelines for agent systems. Production monitoring: latency, accuracy, hallucination rates. Final capstone: a deployed multi-agent enterprise automation system with live demo.

Program 03 / 05

Full Stack AI Engineer

Duration5 Months

LevelIntermediate to Advanced

Core SkillsPyTorch · GenAI · FastAPI · React.js · MLOps · Docker · CI/CD · Cloud Deployment

Tools & PlatformsPyTorch · FastAPI · React.js · MLflow · AWS SageMaker · GCP Vertex AI · GitHub Actions

Who is this for?Job seekers and career switchers who want to become complete AI engineers with full-stack and MLOps deployment skills.

Capstone Outcome: A fully deployed AI SaaS product — complete with React.js frontend, Python/Java backend, LLM integration, and CI/CD pipeline — presented to an industry panel. Placement drive begins immediately after demo day.

Curriculum — Module by Module

AI & ML Engineering

PyTorch: CNNs, RNNs, Transformers. Computer vision with YOLO. NLP: text classification, NER, sentiment. Time series forecasting with deep learning.

GenAI & LLM Engineering

Full LLM stack: prompt engineering, RAG, fine-tuning with LoRA/QLoRA. Multimodal AI. Speech AI: ASR, TTS, voice-enabled applications.

Backend Engineering for AI

Python FastAPI for AI APIs. RESTful design, authentication, rate limiting. PostgreSQL, MongoDB, Redis. Async processing with Celery.

Frontend for AI Applications

React.js for AI app UIs. Conversational interfaces and AI dashboards. Streaming LLM responses. Full-stack integration using our No-Code platform to accelerate delivery.

MLOps & Production Deployment

MLflow, Weights & Biases. Docker, CI/CD with GitHub Actions. AWS SageMaker, GCP Vertex AI. Model monitoring: data drift, degradation detection.

Capstone — Production AI Product

Idea → architecture → development → deployment → monitoring. Build a live SaaS AI product accelerated by our No-Code platform. Pitch to industry panel. Resume, LinkedIn, GitHub, mock interviews — placement drive begins.

Program 04 / 05

No-Code AI Development

Duration2 Months

LevelNo coding required

Core SkillsAI Business Strategy · No-Code App Building · AI Chatbot Integration · OCR · Cloud Deployment · Go-to-Market

Tools & PlatformsNo-Code Platform · GPT APIs · OCR Tools · AWS / Azure · Zapier / Make for AI Workflows

Who is this for?Non-technical founders, business managers, product managers and domain experts who want to build and launch AI products without coding.

Capstone Outcome: Launch a complete, live business AI application — built entirely on our No-Code platform, from idea to deployed product — with no coding required. Includes a product pitch to simulated investors.

Curriculum — Module by Module

AI for Business Leaders

Understanding AI without math — practical concepts for business decision-makers. What GenAI, LLMs, and AI Agents can and cannot do. AI use cases by industry: BFSI, healthcare, retail, government, logistics. AI project planning: ROI frameworks, feasibility assessment, data requirements, vendor evaluation.

Building Apps on No-Code Platform

Platform walkthrough: interface, modules, and capabilities. Visual database schema design — no SQL required. Drag-and-drop UI designer for multi-screen web applications. Mobile app generation for Android and iOS. Third-party API integration: payments, SMS, email, maps, and notifications.

Adding AI Intelligence to Your App

AI chatbot integration into your application. OCR and document intelligence: extract data from PDFs, images, and forms. Multilingual support for regional and global audiences. IVR and voice interface integration. IoT data display and automated alert systems. AI-powered search and recommendation engines.

AI Workflows & Process Automation

Designing AI-first business workflows. Connecting apps, data, and AI using no-code automation tools. Automated reporting, notifications, and approval workflows. Integrating with existing business tools: CRM, ERP, HRMS. Building AI-powered customer service and lead generation pipelines.

Launch, Go-to-Market & Capstone

One-click cloud deployment: AWS, Azure, on-premises. User management, roles, and access control. How to pitch your AI product to investors and customers. Product pricing, subscription models, and go-to-market basics. Final capstone: launch a complete, live business AI application and present to a simulated investor panel.

Program 05 / 05

AI Architect (Premium)

Duration6 Months

LevelSenior / Executive

Core SkillsAI Strategy · Enterprise LLM Systems · Multi-Agent Architecture · Data Engineering · MLOps at Scale · AI Transformation

Tools & PlatformsKubeflow · MLflow · Kafka · Delta Lake · Feast · Seldon · Private LLM Deployments

Who is this for?Senior IT professionals, technology leaders, architects, and CXOs who want to lead enterprise-scale AI transformation and design production AI systems.

Capstone Outcome: Design and present a complete enterprise AI transformation roadmap — including architecture diagrams, vendor recommendations, cost-benefit analysis, and a live product demo — to a simulated C-suite and industry panel.

Curriculum — Module by Module

Enterprise AI Strategy

AI strategy frameworks: build vs. buy vs. integrate. AI governance, ethics, explainability. AI risk management. Designing AI Centers of Excellence.

Advanced LLM Systems

Production LLM systems: latency, throughput, cost optimisation. Private LLM deployments (on-premises, VPC). Enterprise RAG at scale — multi-tenant, multi-domain.

Multi-Agent Enterprise Systems

Agentic AI for enterprise: workflows, approvals, integrations. AI integration with CRM, ERP, HRMS, and finance. Orchestration patterns for complex multi-agent workflows.

Data Engineering for AI

Data pipelines: ETL, ELT, streaming with Kafka. Data lakehouse: Delta Lake, Iceberg. Feature stores. Vector database architecture at scale.

MLOps at Enterprise Scale

ML platforms on Kubernetes: Kubeflow, MLflow. A/B testing and gradual rollouts. LLMOps: monitoring for drift, hallucinations, latency. Cost governance.

Enterprise Transformation Capstone

Rapid enterprise application development using No-Code AI platform. Industry-specific AI blueprints: BFSI, healthcare, government. Case studies: 70–89% development cost savings in real deployments. Final roadmap presentation to simulated board.

All programmes include: Live project builds with real industry data · Industry mentorship · Placement support · Co-branded certification · Cloud deployment experience · Weekly assessments · Hackathons & demo days

Role	Expected Salary
AI Engineer	₹8 – 18 LPA
GenAI Developer	₹12 – 30 LPA
Full Stack AI Engineer	₹10 – 25 LPA
AI Automation Engineer	₹8 – 20 LPA
AI Architect / Tech Lead	₹25 – 50 LPA
No-Code AI Product Manager	₹10 – 22 LPA

Feature	Traditional College	Online Platform	Other Institutes	VedaAI COE
AI Exposure	Year 3–4	After enrolment	Year 2–3	Day 1
GenAI / LLMs	None	Limited	Limited	Core Focus
Real Products Built	Notebooks only	Mini projects	Mini projects	Deployed Apps
MLOps / Deployment	Not covered	Rarely	Rarely	Full Stack
Speed to Job-Ready	4-year programmes	Self-paced	Semester-based	3–6 months
Live Industry Projects	No	No	Some	Always
Startup Incubation	No	No	Limited	Built-in
Govt Alignment	Strong	None	Limited	Active + Strong

Build the Future of AI. Together.

5 AI Programs for Every Level

A Complete Ecosystem — Not Just Training

3-Month AI Product Engineering Internship

Placement & Salary Outcomes

How VedaAI Compares

The People Behind VedaAI

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