AI Engineering Course for DevelopersBuild Production AI Systems with RAG,
AI Agents & MCP

An AI engineering course teaches developers and technical professionals how to build AI-powered software applications using large language models, retrieval-augmented generation, AI agents, evaluation workflows, APIs and deployment practices. Unlike a general AI awareness course, AI engineering training focuses on application development, system design, reliability and production readiness.

Yes. This is a live online AI engineering course delivered via Zoom or Google Meet. Sessions run on weekends to suit working professionals. All sessions are recorded and available within 24 hours for replay.

This programme is designed for Python developers, software engineers, backend and full-stack developers, data scientists moving into LLM applications, data engineers, ML engineers, automation developers, technical founders, and final-year students with Python experience. You need basic Python proficiency — no machine learning background is required.

Yes. Python basics are required. You should be able to write functions, work with APIs, handle dictionaries and lists, and install packages. If you can call a REST API in Python, you are ready. If you are new to Python, complete a free Python basics course first. This programme is not suitable for complete programming beginners.

Yes. This is specifically an AI course for software developers. Backend engineers, full-stack developers, Python developers, and DevOps engineers are the core audience. The curriculum focuses on AI application development, system design and production deployment — not data science or model training.

Five production-grade GitHub projects: (1) RAG-Powered Knowledge Assistant — semantic search over your documents; (2) Multi-Agent Research & Analysis Workflow — autonomous multi-agent pipeline; (3) MCP-Connected AI Assistant — AI connected to live data via Model Context Protocol; (4) Customer Support AI with Guardrails — conversation memory and safety filtering; (5) Deployed AI API — FastAPI, Docker, and cloud deployment with monitoring. All projects are built and deployed during the programme.

Yes. The programme includes a dedicated RAG and Agentic AI course module covering retrieval-augmented generation, vector search, agent workflows, tool use and practical implementation patterns. RAG coverage includes chunking, embeddings, vector databases, semantic search, hybrid search, re-ranking, and production RAG evaluation. Agentic AI coverage includes tool calling, LangGraph stateful agents, multi-agent systems with CrewAI, and human-in-the-loop workflows.

Yes. This is fundamentally an LLM engineering course for developers. It covers LLM API integration across OpenAI, Anthropic, and Google; prompt engineering for developers; embedding models; LangChain and LlamaIndex frameworks; production evaluation with LangSmith; cost management; and hallucination reduction — all focused on building reliable production LLM applications.

Yes. Model Context Protocol (MCP) is covered in depth. You will learn MCP architecture, build MCP servers that connect AI assistants to databases and APIs, and complete a full MCP-connected AI application as one of your five portfolio projects. MCP is becoming the industry standard for enterprise AI connectivity.

For learners searching for AI engineering certification, this programme provides a Technovids certificate of completion — not an independent government, university or vendor certification. The certificate is issued by Technovids Consulting Pvt. Ltd. and is shareable on LinkedIn. Your GitHub portfolio of five production projects typically provides stronger evidence of practical competence.

A verifiable certificate of completion from Technovids Consulting Pvt. Ltd., shareable on LinkedIn. The certificate confirms completion of the AI Engineering Course curriculum and five production projects. It is not a vendor certification from OpenAI or Anthropic, and it is not a government-accredited credential.

This is a live public cohort programme — you join a structured batch with other developers, following a set curriculum on a shared schedule. The 1:1 AI Engineering Mentorship is personalised: individual sessions on your own schedule, a custom learning roadmap, personal code review, and premium pricing. Choose this course for structured group learning at cohort pricing. Choose the mentorship if you need a personalised learning path and individual attention.

This page is for individual learners joining a public cohort. The Production AI Engineering programme is a corporate team training for developer teams of 8–20, delivered as a 5-day on-site intensive or 8-week online cohort, with custom curriculum, team pricing, GST invoicing, and L&D documentation. If you are an individual developer, this page is right for you. If you need to upskill your engineering team, see the corporate programme.

The programme is 80 hours total across 8 modules. Sessions run live online on weekends — Saturday and Sunday — designed for working professionals. Expect 8–10 hours per week including live sessions and project work. Contact us for current batch dates and session timings.

Fees depend on the batch and enrolment timing. We do not publish fees publicly as they may vary by batch and early-bird periods. Book a free AI Career Strategy Call or WhatsApp us to get current fee details, available discounts, and payment plan options.

Yes. Book a free AI Career Strategy Call — our instructor will review your background, discuss your goals, and tell you honestly whether this programme is the right fit. No payment required and no pressure to enrol. You can also WhatsApp us at +91 86183 46384.