Agentic AI Course — Build and Deploy Production AI Agents

Is This Actually For You?

We would rather you find out in thirty seconds than after paying.

Built for you if

✓ You are a backend or full-stack developer who integrates APIs and wants to build complete agent workflows
✓ You work in data or ML , understand models, but have not orchestrated multiple agents in production
✓ You are a DevOps or cloud engineer who wants to turn deployment skill into AI engineering
✓ You are a student or early-career engineer who needs credible project proof, not another certificate
✓ You are already coding and want one structured path instead of forty disconnected tutorials

Not for you if

✕ You have never written code. This is not a no-code or low-code beginner course
✕ You want a certificate without building and deploying anything real
✕ You need live classes or fixed cohort deadlines — this is recorded and self-paced
✕ You are expecting a job guarantee. You get portfolio, interview prep and guidance, not placement promises

What you need before session 1 Basic Python — variables, loops, functions, and enough confidence to read someone else's script. That is the whole prerequisite. The course starts at LLM fundamentals, so no prior AI or ML experience is required.

Sound Familiar?

Before we show you how to build, let's talk about the roadblocks you've been hitting.

💸

You've Spent Lakhs on Courses That Taught You Nothing Practical

Fancy certificates that taught PowerPoint slides about AI, not how to build AI. Zero GitHub projects. Zero production skills. Zero interview confidence.

😰

Job Postings Say 'Agentic AI Experience Required' — And You Don't Have It

LinkedIn is flooded with AI Agent Developer roles at ₹16-52 LPA. But every course you find is either too expensive, too theoretical, or teaches outdated GenAI basics. The gap grows every week.

🔄

You've Watched 100 YouTube Tutorials and Still Can't Build a Complete Agent

Tutorial hell is real. You know bits of LangChain, scraps of RAG, fragments of prompt engineering. But you've never built and deployed a complete, production-grade agent system end to end.

There's a better path. ↓

How We Compare

A factual comparison of how SaptaMind stack up against other educational pathways.

Feature	RECOMMENDED SaptaMind Recordings	Typical Online Bootcamps	University Certificates
Price	✓ ₹4,999 – ₹9,999	₹30,000 – ₹80,000	₹70,000 – ₹1,50,000
Instructor	✓ Founder & Practitioner	Industry trainers	Academic faculty
GitHub Projects	✓ 10+ Production-Grade	3-5 guided projects	1-2 academic capstones
Frameworks Covered	✓ 20+ (LangChain, LangGraph, etc.)	5-8 frameworks	3-5 frameworks
Production Deployment	✓ Docker, ECS, AWS, CI/CD	Limited/optional	Rarely covered
Access Duration	✓ Lifetime access	6-12 months limit	3-6 months limit
Start Date	✓ Today (Instant Access)	Next cohort (wait weeks)	Fixed semester intake
Career Support	✓ Mock interviews + Resume optimization	Placement assistance	Alumni network access

SaptaMind Recordings RECOMMENDED

Price ₹4,999 – ₹9,999
Instructor Founder & Practitioner
GitHub Projects 10+ Deployed
Frameworks 20+ Covered
Deployments Docker, ECS, AWS, CI/CD
Access Lifetime

Typical Bootcamps

Price ₹30,000 – ₹80,000
Instructor Industry trainers
GitHub Projects 3-5 guided
Frameworks 5-8 Covered
Deployments Limited/Optional
Access 6-12 Months

700+ Engineers. Real Results.

Don't take our word for it. Here is what real engineers have achieved.

❝

★★★★★

"I was mass-applying to AI roles with zero confidence. After completing SaptaMind, I had 10 GitHub projects to show. Got 3 interview calls in the first week."

Arjun M. ML Engineer · Bangalore

❝

★★★★★

"I'd spent ₹70K+ on a university AI certification. Learned more practical skills in SaptaMind's Sessions 3-4 alone than that entire 6-month program."

Kavitha R. Data Scientist · Chennai

❝

★★★★★

"The LangGraph + CrewAI modules are gold. I built a multi-agent system for my company's customer support and got promoted within 2 months."

Suresh P. Senior Developer · Pune

❝

★★★★★

"Best ₹5K I've ever spent on education. The RAG pipeline project alone is worth 10x the price."

Neha S. Full Stack Developer · Hyderabad

❝

★★★★★

"Srinivasula sir doesn't just teach — he shows you exactly how he built production systems for real clients. That context is priceless."

Rajesh K. AI Engineer · Mumbai

❝

★★★★★

"I'm from a tier-3 city. Couldn't afford premium bootcamps. SaptaMind gave me industry-ready skills at a price that didn't require a loan."

Divya T. CS Graduate · Warangal

❝

★★★★★

"The Docker + AWS deployment modules are something NO other AI course in India covers. I deploy agents to production now, not just notebooks."

Amar V. DevOps Engineer · Delhi

❝

★★★★★

"Finished the bootcamp, did the mock interviews, optimized my GitHub. Got a ₹18 LPA offer as an AI Engineer. Life changed."

Priyanka G. AI Engineer · Noida

❝

★★★★★

"I've taken courses from Coursera, Udemy, Great Learning. None of them come close to the depth and practical focus of SaptaMind."

Manoj D. Tech Lead · Bangalore

4.8/5

Average Student Rating (★)

92%

Completion Rate (%)

73%

Career Role/Promo in 90 Days

Our Moat Pillars

What sets our Agentic AI bootcamp completely apart from standard theoretical courses.

Founder-Taught, Not Outsourced

Srinivasula Reddy built and deployed production AI agent systems for real estate, healthcare, and enterprise clients. Every recording is taught by the person who actually builds these systems — not a hired presenter reading slides.

10+ Production GitHub Projects

You leave with a portfolio of deployed, documented, production-grade projects. Not Jupyter notebooks. Not toy demos. Employer-tested, interview-ready code on your GitHub.

Concept Depth + Hands-On Code

Deep architectural understanding of agent systems, RAG pipelines, multi-agent coordination patterns, and deployment — the 'why' behind the 'how'. Not copy-paste tutorials.

India's First Comprehensive Agentic Course

20+ frameworks. 22 sessions. Industry-oriented curriculum covering the full stack from LLM fundamentals to agents running in production on AWS. No other Indian course matches this breadth.

Inside the 22 Sessions

Six modules, 50+ hours. From Python and prompting to multi-agent systems running in production on AWS — and something you have actually built at the end of every module.

MODULE 01 · SESSIONS 1–2 Python & Prompt Engineering for AI Work

▼

• Python for AI: data types, OOP, lambdas, map / reduce / filter
• Mutability, memory efficiency and production-grade exception handling
• Prompt patterns: persona, flipped interaction, n-shot, template, meta-language
• Chain-of-thought, self-consistency and least-to-most reasoning
• Calling OpenAI models from Python with safe API-key handling
• Custom GPTs and Gems to package repeatable workflows

You build A reusable prompt library and your first custom agent, plus a Python base you can actually build on.

MODULE 02 · SESSIONS 3–4 LangChain & How RAG Actually Works

▼

• LangChain Expression Language and the | operator for chaining
• Structured output with Pydantic and JSON parsers, plus output fixing
• Memory strategies: buffer, sliding window and summarisation
• Sequential vs parallel chains with RunnableParallel
• Embeddings, semantic search and cosine similarity, explained properly
• Document loaders, recursive chunking and golden test data

You build A LangChain pipeline with structured output, conversation memory and a working retrieval step.

MODULE 03 · SESSIONS 5–8 Ship Real Applications with Coding Agents

▼

• Context engineering: the eight-layer spec-driven workflow
• Generating PRDs, technical design docs, wireframes and task breakdowns
• Claude Code in VS Code: plan mode, review loops, human-in-the-loop
• Slash commands and skills as the agent’s memory and knowledge layers
• Git, GitHub and access tokens for a portfolio recruiters can read
• First AWS deployment: Docker, ECS Fargate, Secrets Manager, CloudWatch

You build A full-stack web application — specced, built with an agent, and deployed live on AWS.

MODULE 04 · SESSIONS 9–12 Production RAG & Your First Multi-Agent System

▼

• Hybrid search, MMR, multi-query retrieval and contextual compression
• Reranking with cross-encoders and metadata-driven filtering
• RAG evaluation: contextual precision, recall, faithfulness, LLM-as-judge
• Playwright scraping into ChromaDB behind a LangGraph orchestrator
• LangGraph state, nodes, edges and conditional routing
• Reflection agents, MemorySaver and OCR fallbacks for messy real inputs

You build A medical report analyser — extraction, parsing, gap analysis and recommendations as four cooperating agents.

MODULE 05 · SESSIONS 13–17 Agent Frameworks, Cloud & Docker

▼

• LangGraph vs CrewAI vs AutoGen: when determinism beats autonomy
• AutoGen assistant and user-proxy agents; CrewAI role-based crews
• MCP and A2A: connecting agents to external systems, with guardrails
• AWS core: EC2, ECS, Lambda, S3, CloudFront, VPC, IAM, Secrets Manager
• Docker, ECR and infrastructure as code with YAML and CloudFormation
• Horizontal scaling, load balancers and blue-green zero-downtime releases

You build A containerised agent service with its infrastructure defined in code, not clicked together in a console.

MODULE 06 · SESSIONS 18–22 Automation, Voice Agents, Fine-Tuning & AgentCore

▼

• Self-hosted n8n: a multi-agent newsletter pipeline that publishes to LinkedIn
• Voice agents with Bolna AI: guardrails, tone and live call workflows
• WhatsApp agents on the Meta developer stack, with approval steps
• Observability using LangSmith, Arize, LangFuse and OpenTelemetry
• Fine-tuning with LoRA and PEFT, 4-bit quantisation and JSONL datasets
• AWS Strands and Bedrock AgentCore for serverless agent deployment

You build A voice agent, a WhatsApp agent and a fine-tuned model — each deployed and each traceable.

Ready to start? → Enroll Now — ₹4,999

Join 700+ engineers already learning.

Here's Everything Inside Your Enrollment

We don't hide value. Here's a transparent breakdown of everything you unlock.

✓ 22 HD Recorded Sessions (50+ hours) ₹50,000

✓ 10+ Production GitHub Project Repositories ₹20,000

✓ LangChain, CrewAI, LangGraph, AutoGen Deep-Dives ₹15,000

✓ Docker + AWS Deployment Modules ₹10,000

✓ RAG Pipeline Architecture Masterclass ₹8,000

✓ AWS Bedrock Integration Workshop ₹7,000

✓ Lifetime Community Access (WhatsApp) ₹5,000

✓ Certificate of Completion ₹3,000

Total Value: ₹1,18,000

Your Price Today:

₹4,999

That's 96% off. Not a typo.

Claim Your Spot →

83 of 100 special launch seats remaining.

Pricing Tiers

Pick the tier that fits your learning style. Lifetime updates guaranteed.

BASIC

Course Access

₹4,999 ₹6,999

✓ 22 HD session recordings
✓ 10+ GitHub project repositories
✓ Community access (WhatsApp)
✓ Certificate of completion
✓ Lifetime access

Get Course Access

Prefer WhatsApp? Message us directly

Success Pack

₹6,999 ₹9,999

✓ Everything in Course Access +
✓ Weekday doubt clarification sessions
✓ Priority community support
✓ Direct Q&A thread access

Get Success Pack

Prefer WhatsApp? Message us directly

BEST VALUE

Career Pack

₹9,999 ₹14,999

✓ Everything in Success Pack +
✓ 1-on-1 resume building sessions
✓ Mock interview practice
✓ Career strategy guidance calls
✓ LinkedIn & GitHub optimization

Get Career Pack

Prefer WhatsApp? Message us directly

🔥 Special launch pricing for first 100 students only. 83 seats remaining

Frequently Asked Questions

The things people actually ask before paying, answered straight. If yours is not here, WhatsApp us.

You should be comfortable writing a function, using loops and dictionaries, and reading someone else's script without panicking. Session 1 covers the specific Python the course leans on — classes, lambdas, map and filter, exception handling, file operations — but it is a refresher, not a first programming course. You need no prior AI or machine learning background; the course starts at LLM fundamentals.

Because it is recorded rather than live. These are the recordings from a completed cohort — the same sessions, the same projects, the same instructor, not a trimmed-down version. What you are not paying for is scheduled instructor hours, a sales team and a placement desk. That is the whole difference.

Yes, a little, and you should know before you buy. You will need your own LLM API access — OpenAI, Anthropic or Gemini — which is pay-as-you-go and costs a small amount at coursework volumes. The deployment sessions use an AWS account; most of what you build fits inside the free tier, though some services bill. The coding-agent sessions work with either a Claude subscription or API credits, and the course walks through both. Fine-tuning runs on Google Colab's free GPU tier, and n8n runs locally at no cost. Wherever a free or cheap path exists, the sessions show it.

22 sessions and 50+ hours of recordings. It is self-paced with lifetime access, so you set the schedule. Budget more than 50 hours in practice — you are building alongside the sessions, and the projects are where the time actually goes.

So you can pause, rewind and rewatch the parts that do not land the first time, start today instead of waiting for a cohort, and pay recorded pricing rather than live-cohort pricing. The trade-off is honest: the base tier has no live Q&A. If you want scheduled help, the Success and Career packs add weekday doubt-clarification sessions.

They are applications, not notebooks. A full-stack web app specced and deployed on AWS. A medical report analyser built as four cooperating agents that extract, parse, spot deviations and recommend. A RAG system that scrapes live sites with Playwright into ChromaDB behind a LangGraph orchestrator. A containerised agent service with its infrastructure defined in code. A voice agent, a WhatsApp agent and a fine-tuned model. All of it goes to your GitHub, deployed and documented — which is what an interviewer can actually click on.

YouTube gives you fragments that each assume a different starting point. This is one path through 22 sessions: concept, then code, then deploy, then portfolio. The parts YouTube rarely covers are the ones that decide interviews — evaluation, observability, guardrails, cost, and getting something into production and keeping it there.

Frameworks churn; the architecture underneath does not. State management, retrieval and reranking, evaluation, memory, tool use, deployment and observability are the same problems whichever library is fashionable this quarter. The course teaches those alongside the current tools — LangGraph, CrewAI, AutoGen, MCP, Bedrock AgentCore — and your access includes future content updates.

The course content is identical in all three: 22 sessions, every project, lifetime access. What changes is how much help you get. Course Access (₹4,999) includes the community. Success Pack (₹6,999) adds weekday doubt-clarification sessions, priority support and a direct Q&A thread. Career Pack (₹9,999) adds the career layer — one-on-one resume work, mock interview practice, strategy calls, and LinkedIn and GitHub optimisation. If you only want the material, the base tier is the whole course.

Course Access includes the community. Success Pack and Career Pack add weekday doubt-clarification sessions with the teaching team, priority support and a direct Q&A thread. Every project also ships with a working reference repository, so there is always something correct to compare your code against.

Yes — a certificate of completion once you finish the modules and submit your capstone. Worth being straight with you though: a certificate is not what gets you hired for an agentic AI role. The deployed projects on your GitHub are. Treat the certificate as a record and the portfolio as the actual outcome.

Pick a plan and message us on WhatsApp; we confirm access from there. For company-funded seats we issue GST invoices under YENNPRI SOLUTIONS LLP, GSTIN 36AADFY9404H1ZY. Email yennapusa@saptamind.com for bulk or corporate enrolment.

Build AI Agents That Actually Ship.

Watch: How This Bootcamp Builds Production AI Agents in 22 Sessions

Is This Actually For You?

Built for you if

Not for you if

Sound Familiar?

You've Spent Lakhs on Courses That Taught You Nothing Practical

Job Postings Say 'Agentic AI Experience Required' — And You Don't Have It

You've Watched 100 YouTube Tutorials and Still Can't Build a Complete Agent

How We Compare

700+ Engineers. Real Results.

Our Moat Pillars

Founder-Taught, Not Outsourced

10+ Production GitHub Projects

Concept Depth + Hands-On Code

India's First Comprehensive Agentic Course

Inside the 22 Sessions

MODULE 01 · SESSIONS 1–2 Python & Prompt Engineering for AI Work

MODULE 02 · SESSIONS 3–4 LangChain & How RAG Actually Works

MODULE 03 · SESSIONS 5–8 Ship Real Applications with Coding Agents

MODULE 04 · SESSIONS 9–12 Production RAG & Your First Multi-Agent System

MODULE 05 · SESSIONS 13–17 Agent Frameworks, Cloud & Docker

MODULE 06 · SESSIONS 18–22 Automation, Voice Agents, Fine-Tuning & AgentCore

Here's Everything Inside Your Enrollment

Pricing Tiers

Course Access

Success Pack

Career Pack

Srinivasula Reddy Yennapusa

Frequently Asked Questions

Still Have a Question?

Talk to us first

The AI Agent Wave Won't Wait.