AI Development Workflows Training in Amritsar
AI-Driven Development Workflows & Tooling — our AI Development Workflows course in Amritsar, 12 Weeks. Supercharge your development workflow with AI. Learn to integrate Copilot, build custom AI agents, automate DevOps pipelines, and architect intelligent tooling that amplifies team productivity.
Course Overview
AI is not replacing developers. Developers who use AI are replacing developers who do not. This course is about integrating AI into every part of your development workflow. Not just writing code with Copilot, but using AI for code review, testing, DevOps, architecture decisions, and team productivity. We start with the tools: GitHub Copilot, Cursor, Codeium, and how to prompt them effectively.
DevOps is where AI saves hours every week. You will generate CI/CD pipelines, Dockerfiles, Terraform configs, and Kubernetes manifests with AI. Feed error logs to LLMs for root cause analysis. Automate security scanning and dependency analysis. Build pipelines that self-heal when they fail, suggesting fixes instead of just reporting errors.
Architecture and design are next. AI can recommend patterns, generate OpenAPI specs, optimize database schemas, and turn Figma designs into React components. You will use AI for accessibility auditing, large-scale refactoring, and codebase understanding. This is not about letting AI make decisions for you. It is about using AI to surface options faster so you make better decisions.
The final module is custom tooling. You will build domain-specific AI agents with LangChain, create RAG pipelines that embed your codebase for retrieval-augmented generation, and automate team workflows like PR triage and sprint planning. The capstone is a complete AI developer toolchain with custom agents, automated testing, and deployment bots. Twelve weeks, and your workflow is unrecognizable.
Curriculum Blueprint
Weekly module breakdown covering AI-assisted coding, DevOps automation, design intelligence, and custom tooling.
- LLM-assisted development: GitHub Copilot, Cursor, and Codeium setup, configuration, and daily workflow integration
- Prompt patterns for code: zero-shot generation, few-shot examples, context injection, and iterative refinement
- When AI helps and when it hurts: understanding hallucinations, context limits, and when to trust AI-generated code
- Code review automation: static analysis with AI, security vulnerability detection, and refactoring suggestions
- Test generation: AI-powered unit test creation, edge case discovery, and mutation testing augmentation
- Documentation automation: inline doc generation, API spec extraction, and changelog summarization
- Multi-file editing with Cursor: codebase-wide refactoring, multi-file context, and Composer workflows
- Debugging with AI: feeding error traces, stack traces, and logs to LLMs for root cause analysis
- First project: build a feature end-to-end using AI for planning, coding, testing, and documentation
Tools Covered
Prerequisites
- Fundamental understanding of software development lifecycle and Git workflows
- Basic exposure to cloud platforms (AWS, Azure, or GCP) concepts
- Comfortable with at least one programming language and basic terminal usage
- Absolute commitment to master core underlying software engineering over syntax rules
Lab Access
- Cloud sandbox environment
- Real production server access
- Local AI model playground
- 24/7 Git repository access
Quick Inquiry
Interested? Drop your details and we will reach out.
Common Questions
The things people ask us on the phone before they enrol — answered the same way we would answer them there.
There is no separate price for it. WebPrims charges one fee — ₹4,500 / month — and it covers any course in the catalogue, so the AI Development Workflows course works out at about 3 months — around ₹13,500 in total. No admission fee, no registration fee, and the certificate is included.
Monday to Saturday, with batches starting at 11:00 AM, 1:00 PM, 3:00 PM and 5:00 PM. Each slot runs up to two hours — sometimes a session finishes early, never late. That works out at roughly 144 hours of class time across the 12 Weeks. Pick whichever time fits around college or work, and move to another later if your timetable changes; it is the same AI Development Workflows syllabus in each. We are closed on Sunday.
12 Weeks of taught material, which is about 3 months of AI Development Workflows classes. That is the pace of the syllabus; how long you actually take depends on how often you turn up, and nobody is pushed to keep up with the batch.
You need to already write code for a living or close to it. This course adds AI to an existing practice; it does not teach the practice.
A changed way of working: AI in the editor, in code review and in the deployment pipeline, plus custom agents doing the parts of your job that never needed a human.
Both are possible, and the difference is review discipline, which is most of what we drill. Generating code was never the hard part — knowing what to accept is.
Yes. Book a free demo class and sit in a real AI Development Workflows session — one that was running anyway, not a presentation arranged for you. Write some code on one of our machines, ask the students already in it what it is like, and decide afterwards. Nothing to pay and no obligation.
Something here not answered? Ask us directly or book a free demo class and put it to the AI Development Workflows mentor in person.
Weighing this up against something similar? AI Courses in Amritsar sets them side by side and says which suits whom.