Keen Infotech · Online and classroom training
Go beyond prompt demos and learn to design, build and deploy intelligent applications that solve real business problems. This practical program takes you from Generative AI fundamentals to production-ready agents and automated workflows.
Certificate of Completion (verifiable and shareable on LinkedIn)
Live doubt-clearing sessions (2x per week)
1:1 mentorship calls (bi-weekly, with an AI engineer)
Private Discord/WhatsApp community for peer support and networking
Real client-style, portfolio-ready projects
Weekly assignments and auto-graded quizzes
Mock interviews and resume/LinkedIn review
Job and freelance assistance with referrals and proposal templates
Lifetime access and free updates as AI tools evolve
Downloadable prompt libraries, code templates and cheat sheets
Recorded sessions to watch at your own pace
Capstone Demo Day presentation
Weeks 1–4
What is AI? Narrow AI vs General AI; Generative AI across text, image, audio, video and code; Generative AI vs traditional AI/ML; AI agents vs chatbots vs GenAI tools; reactive, deliberative, hybrid and multi-agent systems; agentic architecture; real-world examples; the future of Generative and Agentic AI.
How LLMs are trained; tokenization, embeddings and context windows; prompt engineering basics; temperature, Top P and Top K; function calling, structured output and streaming; open-source vs closed-source models (Llama, Mistral, GPT, Claude, Gemini and DeepSeek). Practical work with OpenAI Playground, Claude, Gemini, DeepSeek and Hugging Face.
Zero-shot, one-shot and few-shot prompting; Chain of Thought, Tree of Thought, ReAct and role prompting; prompt templates and optimization; meta-prompting and system prompt design. Projects: Resume Generator, Email Writer, Blog Generator and AI Prompt Library.
Text-to-image with Midjourney, DALL·E, Stable Diffusion and Flux; Photoshop AI, Canva AI and Remove.bg; Sora, Runway, Pika, Kling and Luma; HeyGen, D-ID and Synthesia; Suno, ElevenLabs and Udio; text-to-3D and AI design tools. Project: AI Content Studio with image, caption and voiceover generation.
Weeks 5–8
OpenAI, Gemini, Claude, Groq, DeepSeek and OpenRouter APIs; API keys, authentication, rate limits, pricing and model selection.
Python basics, functions, classes and file handling; JSON, Requests, environment variables, virtual environments and pip. Practical work: call an OpenAI API and build a chatbot.
LangChain models, prompt templates, chains, output parsers, memory, tools, agents and callbacks. Project: AI Research Assistant. LangGraph StateGraph, nodes, edges, multi-agent workflows, memory and checkpointing. Project: Multi-Agent Customer Support.
MCP architecture, clients, servers, resources, tools, prompts, authentication and security. Practical work: create an MCP server, connect Claude Desktop and ChatGPT, and build a custom tool.
n8n installation, workflows, triggers, AI nodes and OpenAI integration; Zapier AI-powered Zaps; Make.com scenarios and AI modules; UiPath and AI RPA basics; Gmail, Google Sheets, WhatsApp, Telegram, Slack and Notion integrations. Projects: AI Email Reply Bot, Lead Generator, CRM Automation and AI Automation Agency Starter Kit.
Weeks 9–12
Vector databases, embeddings, chunking, metadata, retrieval and ranking; ChromaDB, FAISS, Pinecone, Qdrant and Weaviate. Projects: PDF Chatbot and Company Knowledge Bot.
LangChain, LangGraph, CrewAI, AutoGen, OpenAI Agents SDK, PydanticAI and SmolAgents; framework comparison by performance, use cases, pros and cons; fine-tuning basics and LoRA for open-source LLMs.
Planner, Research, Coding, Reviewer and Manager agents. Project: AI Software Company multi-agent simulation.
Speech-to-text, text-to-speech, voice assistants and live conversation with ElevenLabs, Whisper, Deepgram and AssemblyAI. Project: AI Call Assistant. OCR, image analysis and object detection with GPT Vision, Gemini Vision and Claude Vision. Projects: Invoice Reader and Medical Report Analyzer.
Browser automation with Playwright, Browser Use and computer-use agents; LinkedIn Automation and Web Research Agent projects; Gmail, Google Calendar, Drive, Docs, Notion, Slack and Discord integrations; Personal Assistant and Meeting Scheduler projects.
Short-term, long-term, vector, user-profile and session memory. Project: Personal AI Assistant. Prompt injection, jailbreaks, data leakage, API security, authentication and authorization.
Weeks 13–16
Docker, Docker Compose, Git, GitHub, GitHub Actions, Jenkins CI/CD, VPS deployment, Nginx, SSL and monitoring.
Logging, monitoring, retry logic, error handling, caching, cost optimization and scaling.
AI ethics and responsible AI; Bubble + AI, FlutterFlow + AI and Voiceflow; AI agent marketplaces; building an AI SaaS product from idea to MVP.
AI HR Recruiter; AI Travel Planner (MERN + AI Agent); AI Customer Support System; AI Sales Assistant; AI Medical Assistant demo; AI Finance Assistant; AI Research Agent; AI Code Review Assistant; AI Content Studio; AI Marketing Automation. Demo Day: present your capstone to the community.
Portfolio building, GitHub profile, LinkedIn optimization, AI Engineer resume, client communication, proposal writing, Upwork, Fiverr, starting an AI automation agency, interview preparation, AI Engineer roadmap, mock interviews and live mentor resume review.
| Month | Focus | Key Outcome |
|---|---|---|
| 1 | Gen AI, LLMs, Prompting, Media Generation | Prompt, generate content and build simple AI tools |
| 2 | APIs, LangChain/Graph, MCP, Automation | Build agents and automate workflows with n8n/Zapier |
| 3 | RAG, Multi-Agent, Voice/Vision AI | Build production-grade multimodal agents |
| 4 | Deployment, Capstone, Career | Become job/freelance ready with a live portfolio |
Total Duration: 4 Months (16 Weeks) | Level: Beginner → Job-Ready