Generative AI Course in Manikonda
For engineers and builders in Manikonda, this course goes past prompting into the engineering behind production GenAI.
- Live cohorts, not recordings
- Practitioner-taught
- Community & placement
- Lifetime access
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Built for Manikonda builders
Every module ends with something working — a RAG pipeline, an agent, an eval suite — built live alongside peers from Manikonda and beyond. This goes past prompting into the actual engineering behind production GenAI.
Curriculum breakdown
Module 1: Prompt engineering and structured chains
Manikonda students learn structured prompt design and function calling, not just one-off prompt tricks.
Topics covered
- Prompt architecture and function calling
- Structured output validation
- Multi-step prompt chains
Module 2: RAG pipelines with vector databases
Building a working retrieval-augmented generation pipeline, end to end, as a Manikonda student.
Topics covered
- Chunking and ingestion strategy
- Vector database selection and indexing
- Retrieval quality evaluation
Module 3: Agents and tool use
Building an agent that uses tools reliably, for Manikonda students moving beyond single-turn prompting.
Module 4: Evals, guardrails and deployment
Shipping what you've built with monitoring and safety guardrails in place.
How the cohort runs
Format and schedule
Live, project-based cohort
Fully online, live over Zoom, for Manikonda learners and peers across every module.
Who this course is for
Engineers and builders
Manikonda engineers who want the architecture behind production GenAI, not just API basics.
Technical founders
Manikonda founders building an LLM-powered product who need to move past a fragile prototype.
Outcomes and support
Portfolio project
Manikonda students leave with a working RAG or agent project they can show employers.
Prerequisites
Basic Python recommended
The course focuses on architecture decisions for Manikonda students, not syntax fundamentals.
Note
Covers OpenAI, Anthropic (Claude), and open-source models, so Manikonda students aren't locked into one provider's mental model.
Quick answer
The Generative AI Course in Manikonda is a hands-on, project-based program covering prompt engineering, RAG pipelines, agents and evals — the engineering behind production LLM systems, not just prompting tricks. It's built for Manikonda engineers and technical founders who want to move a fragile prototype into something production-ready, and it's worth it if your goal is a working portfolio project, not just theoretical understanding of how LLMs work.
How this compares to free YouTube tutorials or API documentation
- You build a working RAG pipeline, agent and eval suite during the cohort, not just watch someone else build one
- Covers OpenAI, Anthropic (Claude) and open-source models together, so Manikonda students aren't locked into one provider's documentation and mental model
- Live feedback on your architecture decisions from a practitioner shipping production GenAI systems, not a comments section
- Structured progression from prompting through RAG, agents, evals and deployment, instead of scattered standalone tutorials
Why Manikonda builders choose Deepak Suhag
Taught by someone who ships production GenAI systems for clients — not a course built from documentation alone.
How it works
Simple, transparent process — from first contact to measurable results.
Enrol & Onboard
Instant portal access, cohort Slack invite, and full session calendar on day one.
Live Sessions
Weekly Zoom sessions with real campaign walkthroughs, live dashboard reviews, and Q&A.
Build & Get Feedback
Hands-on assignments on your own campaigns with direct 1:1 feedback from Deepak.
Graduate & Network
Industry certificate, alumni community, job board access, and ongoing placement support.
Tools & platforms
The exact stack I use daily across growth marketing, web development, AI, and automation — no guesswork, no vendor lock-in.
Why work with Deepak
Here's what makes this different from every other option in Manikonda.
Taught by a practitioner
Every module comes from live campaigns with real budgets — not textbook theory or outdated slides.
Live cohorts, not recordings
Ask questions in real time, get live feedback on your campaigns, and learn with a cohort of peers.
Practitioner-led curriculum
Real ad accounts, real case studies, real budgets — everything relevant to where you work, wherever that is.
Career-ready outcomes
Portfolio projects, alumni Slack, and direct referrals to companies actively hiring in your city.
Everything you need to know
Still have a question that isn't answered here? Reach out directly — I respond to every inquiry personally.
Ask a question01Do I need Python experience in Manikonda?
Basic Python is recommended — the course focuses on architecture, not syntax.
02Which LLM providers do you cover?
OpenAI, Anthropic (Claude), and open-source models.
03Is this available for Manikonda learners remotely?
Yes — the cohort runs fully online, live over Zoom.
04Do I get a project I can show employers in Manikonda?
Yes — a working RAG or agent project is part of the curriculum.
05How much does the Generative AI course cost for Manikonda students?
Fees are confirmed on a short intro call since they can vary by cohort and current offers. Manikonda students should book a call to get accurate, current pricing.
06What's the difference between this and free YouTube tutorials on ChatGPT or LangChain?
Free tutorials usually show a narrow demo without covering evals, guardrails or deployment. This course walks Manikonda students through the full path — prompting, RAG, agents, evals and shipping safely — with live feedback on your own project, not just a video to watch passively.
07Do I need to already know machine learning to join from Manikonda?
No ML background is required. Basic Python is recommended since the course focuses on architecture decisions rather than syntax fundamentals, but Manikonda students coming from a general software background can follow along.
08Do I get a certificate or portfolio project?
Yes — Manikonda students leave with both a certificate of completion and a working RAG or agent project they can show employers, which matters more than the certificate itself in most technical interviews.
09What if I fall behind or miss a session?
Sessions are recorded, and since every module builds toward a working deliverable, Manikonda students can catch up on missed material before the next module starts without losing the thread of the project.
10Does this course help with GenAI job opportunities or salary in Manikonda?
Production GenAI experience — RAG pipelines, agents, evals — is in high demand relative to the supply of engineers who've actually shipped it, rather than just called an API once. The portfolio project from this course is built specifically to be something Manikonda students can walk through in an interview.
I started teaching because I was frustrated seeing marketers memorise theory they'd never use. Every lesson I teach comes from a live campaign, a real mistake, or a real win. You'll leave with skills you can use tomorrow morning.