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From SDE To AI EngineerShip Production-ready AI Systems In 10 Weeks
For working professionals who see AI advancing fast and want to transition into serious, high-impact AI engineering roles. Build production-ready systems using agents, RAG, Evals, and real-world enterprise workflows. No prior AI or LLM experience required.
LanguageEnglish
Starting On26 September
Schedule (IST)Sat + Sun, 8-10:30 PM
SSRVJ
2200+ Careers Transformed
Agentic AI Depth
Learn how agents think, plan, and act through algorithm-first principlesEval-Driven Engineering
Design, test and iterate AI systems using rigorous evaluation frameworksExecution-First Approach
Ship deployable systems in every module with real-world constraints & trade-offsTarget AI Roles
Build skills aligned with expectations of frontier AI labs and product teamswhy this course
We Built The Course We Couldn't Find
“
I want a course that doesn't waste my time.
I have a full-time job. I need this to move swiftly without sacrificing quality.
Too many frameworks. I just want to learn what's actually used in production.
I want a refresher on Python & ML basics, not a whole course on them.
I want to understand the fundamentals of LLMs, RAG, and Evals before I touch code.
I want real, production-grade projects, not just calling OpenAI APIs.
No more scattered tutorials like YouTube. I want structure, mentorship and quality projects all bundled into one course.
I want to invest in a quality education, not gamble ₹1L+ on a course that may not deliver.
the verdict
This Is That Course.
Ten weeks. Fundamentals first, Enterprise-grade AI Systems built end-to-end, nothing you'll never use on the job, highest ROI.
Built on the traditional software engineering foundation you already know.
what's actually different here
Built For Engineers Who Already Ship Production Code.
10 Weeks High-Intensity Cohort
Live weekend sessions, ~3 hours each, requires sustained pace and real accountability to complete this cohort.
Designed by AI Industry Experts
Curriculum and case studies shaped by engineers who've shipped AI systems at companies like Uber, Qdrant, Google, etc.
Built Backward from AI Failure
Designed using MIT research on why AI systems break after launch, training engineers to fix those exact issues.
Practical Job Assistance
Career guidance and Industry connections to help you land your next AI engineering role.
Senior Coding Shuttle Community
A network of working professionals pushing toward AI roles, sharing knowledge and opportunities.
AI for every career stage
Who Is This Cohort For?
We have helped place 4570+ students in 470+ companies And Now It's your turn
the opportunity
The Career Outcomes You Can Unlock
Apply to Frontier AI Roles
Break into FDE, AI Architect, and AI product roles across top labs, startups, and high-growth AI teams.
50-80% Higher Salary Potential
Software engineers with AI skills are seeing 50-80% higher salaries than traditional developers.
1,800+ Alumni Placed
Our placements across 470+ hiring partner companies, from fast-growing startups to global tech firms.
FROM FUNDAMENTALS TO PRODUCTION
The Structured Agentic AI Curriculum You'll Follow
WEEK 1
Python for AI & LLM Fundamentals
Learn the fundamentals of Python and LLM internals to build strong foundations for AI engineering.
Python
FastAPI
Transformers
What You'll Learn
Python Funamentals (functions, classes, objects)
Async Python, APIs & Streaming Responses
Transformer Internals & Tokenization, Vectorization and Attention
End-to-end LLM lifecycle & Model Tiering
Outcome:Build your first LLM-powered App with a streaming backend and cost tracking
WEEK 2
Retrieval-Augmented Generation (RAG) Foundations
Learn to ground LLM responses in factual data using vector search and retrieval engineering.
pgvector
Embeddings
What You'll Learn
Embeddings & Vector Geometry Basics
Multi-Tenant Isolation Patterns
Vector Databases & Indexing Strategies
Document Parsing & Optimal Chunking
Outcome:Build retrieval systems that answer questions factually without hallucinating.
WEEK 3
Enterprise-grade RAG Pipelines
Push past naive vector search with hybrid strategies, re-ranking, and dynamic query routing.
BM25
RRF
What You'll Learn
Hybrid Search (Semantic + Keyword)
Cross-Encoder Re-Ranking Strategies
Query Expansion & Graph RAG Basics
Outcome:Master enterprise-grade search techniques used by top AI product teams.
WEEK 4
AI Agents & State Machines
Move from stateless prompts to autonomous agents capable of reasoning and using external tools.
ReAct
Multi-Agent Orchestration
LangGraph
What You'll Learn
LLM vs Agent vs Multiple Agents
The ReAct Loop & Reliable Tool Calling
Prompt Chaining, Orchestration, Routing
Building State Machines with LangGraph
Outcome:Ship a tool-calling agent that pauses for human approval and resumes seamlessly.
WEEK 5
Evals & Observability
Stop deploying on 'vibes.' Learn end-to-end tracing, evaluation datasets, and CI/CD gates for production AI.
Langfuse
OpenTelemetry
RAGAS
DeepEval
What You'll Learn
End-to-End Tracing: Capturing LLM inputs, tool execution & retrieval steps
Unit Economics: Tracking token cost and latency breakdown per request
Golden Datasets & LLM-as-a-Judge Scoring Methodologies
Evaluating Agents, RAG Pipelines & Tool Call Trajectories
Outcome:Trace production execution step-by-step and make underperforming prompts physically unable to ship.
ai tools you'll master
Industry-Leading AI Tools In Your Hands
Fundamentals over Frameworks — We use latest AI stack as the medium, but heavily focus on fundamentals that transfer across models, frameworks, and tools so your skills remain relavant as the AI ecosystem evolves.
Qdrant
Vector DB
pgvector
Vector DB
LangChain
Framework
LlamaIndex
Framework
CrewAI
Agents
Streamlit
App Framework
Langfuse
Observability
LangSmith
Observability
FastAPI
Framework
LangGraph
Framework
Redis
Memory
RAGAS
Evals
GitHub Actions
CI/CD
MCP SDK
Protocol
Docker
Deployment
Ollama
Model Serving
Hugging Face
Models
OpenAI Whisper
Voice AI
AWS
Cloud
everything you build
1 Capstone + 9 Projects Built From Scratch
Capstone Project
Build & deploy a complete entrprise-grade MVP with agents, evals & observability dashboard.
Docker
AWS
Observability
The AI Gateway
A streaming, non-blocking chat backend with real-time token usage and cost tracking.
FastAPI
Streaming
Cost Tracking
The Knowledge Engine
A context-aware RAG pipeline, backed by a local vector store, that accurately answers questions over complex documents.
RAG
pgvector
LangChain
The Enterprise Search Engine
A multi-tenant, re-ranked hybrid search system for enterprise data.
Hybrid Search
Multi-Tenant
Pinecone
The Persistent Operator
An autonomous, tool-calling agent that takes real actions and remembers customer context via Redis-backed persistent memory.
LangGraph
Redis
Tool Calling
The Regression Gate
An automated eval harness for your ticket classifier that scores AI responses and blocks CI/CD deploys on regression.
LangSmith
RAGAS
CI/CD
The Audited Tool Bridge
Wrap internal systems into heavily audited tools and expose them through a standardized multi-tool agent bridge.
MCP
CrewAI
Docker
The Specialist Model
Fine-tune an open-weight model end-to-end and benchmark it against frontier APIs on a head-to-head dashboard.
LoRA/QLoRA
Weights & Biases
The Dual-Agent Supervisor
A secure, scalable dual-agent supervisor system that survives a live provider-outage recovery drill.
Multi-Agent
Reliability
Failover
The Multimodal RAG Engine
A multimodal RAG system with vision and voice data channels that extracts structured data and tracks cost-per-ticket on a live dashboard.
Vision
Voice AI
Live Dashboards
What's Included
More Than A Course, An AI Engineering System
20+ Live Classes
Learn directly from Anuj Kumar Sharma, real-time interaction, Q&A, and doubt clearing.
10+ Real AI Case Studies
Reverse-engineer how OpenAI, Anthropic & other AI teams ship.
Homework Assignments Every Week
40+ hands-on assignments to turn concepts into production-ready skills
1:1 Mentor Doubt Calls
Book live 1:1 sessions with mentors when you're stuck.
9 Weekly Projects + 1 Capstone
One project a week, and 1 major capstone project included.
Private Cohort Community
Network with peers from different industries and backgrounds.
Evals & AI System Design
Build enterprise-grade scalable AI systems with evaluation-first principles.
100% Focused on FDE & AI Roles
Every lecture targets exactly what these interviews test for.
Taught by Industry Experts
Learn directlry from AI industry experts who've shipped production AI solutions.
Job Assistance
Break into AI roles with dedicated resume building & AI interview prep webinars.
Exclusive Hackathons
Compete in exclusive AI hackathons to test your skills and win prizes.
Certificate of Completion
Share your new skills with your employer or on LinkedIn.
we stand out
Where Others Stop, Coding Shuttle Takes You Further
| What You Get | Other Courses |  This Live Cohort |
|---|---|---|
| Live Sessions & Mentorship | No mentorship | Live + 1:1 mentorship |
| Structured AI Roadmap | Scattered resources | AI experts designed |
| Real-World AI Projects | Mostly demos | 10+ real-world projects |
| Code Reviews & Doubt Solving | No feedback | 24/7 doubt support |
| System Design for AI | Rarely covered | Dedicated AI system design |
This course is for you if
You want to use your existing backend and software engineering skills to become effective in AI Engineering, FDE, or AI-focused product roles.
You want to move from building traditional software to building and shipping production AI systems.
Not toy projects, you want to build real AI applications with LLMs, RAG, agents, evals, and production-grade frameworks.
You're a working in technical domain (SDE/QA/Support) and looking to upskill with AI mastery.
You want hands-on AI engineering experience, guided by people who've shipped AI products in production.
The Rise Of AI Engineering: A New Career Path For The Native-AI Era
Forbes describes the shift toward model-mediated software, where engineers combine models, tools, retrieval, workflows, and evaluation to build reliable production systems.
”Instructor
Learn from Industry Experts
Anuj is a software engineer and the founder of Coding Shuttle, where he has personally taught 500,000+ engineers Java, Spring Boot, AI and backend system design. 7+ years of experience building production backend systems, including at Amazon and Urban Company. This course exists because Anuj needed to add an AI layer to Coding Shuttle's own production platform and found no course teaching AI engineering the way a working backend engineer actually needs it at an affordable price.
Founder & CEO @ Coding Shuttle
testimonials
What our students are saying.
"From concepts to real AI systems"
Anuj's lectures go beyond theory, I was able to apply LLM fundamentals and RAG concepts directly in my workflow after building the Lovable clone project here.
Sahil Naik
Software Developer, Oracle
"Well-structured from basics to advanced"
The course is exceptionally well-structured and comprehensive, blending foundational concepts with advanced material for a thorough grasp.
Roshan Kumar
Software Engineer, PwC
"Projects that feel like real products"
Building weekly projects, including a Lovable-style clone, helped me understand how real AI products are structured and shipped.
Jyoti Bharti
Software Engineer, Johnson Controls
"Built and shipped a real AI project"
This course helped me build a production-grade Lovable clone AI application from scratch, something I could confidently showcase at work.
Touhid Sayed
Senior Analyst, Capgemini
"Strong fundamentals + real support"
The program builds strong backend and system design fundamentals, and the support system ensures you never get stuck.
Arunima Saxena
Senior Software Test Analyst, Accenture
"Perfect for beginners like me"
This course is perfect for beginners struggling to get started. Well-structured, covers the essentials, with live weekend classes too.
Anandini Tripathy
Product Engineer, Cummins
"Production-grade thinking, not tutorials"
The course teaches how to think like an engineer building production systems, not just follow along tutorials.
Aiman Shakeel
Senior Software Engineer, Cognizant
"Hands-on learning that sticks"
Implementing concepts like RAG and system design while coding made everything click and stay long-term. Anuj explains concepts while implementing them in code, a hands-on approach that makes real-world development easier to grasp.
Aanshi Vishwakarma
Lead Engineer, HCLTech
"Confidence to build production-grade systems"
This program built real confidence in backend fundamentals and system design. I can now design AI-powered systems instead of just consuming APIs.
Satyansh Shukla
Lead Software Engineer, Accolite
"Worth it for real-world AI skills"
A bit pricey, but completely worth it. The ability to build production-ready AI systems and not just demos made all the difference.
Vatsal Adhiya
SDE Intern, Texas Instruments
"Well-structured with real examples"
The course is well-structured and packed with real examples. What sets it apart is the focus on actual applications rather than just theory.
Rahul Kumar
Software Engineer, BPCE NATIXIS
"Hands-on, not just theory"
Unlike courses that stay broad and theoretical, this one is practical and project-based, with an engaging style built around real projects.
Abhigyan
Software Engineer, OneTrust
"Clear path to applying AI in work"
The structured approach made it easy to apply AI concepts in real-world scenarios, especially in building scalable systems.
Abhishek Suvarnakar
Software Development Engineer, Equilend
"Consistency that compounds skills"
Weekly assignments and system-building exercises helped me truly internalize backend and AI engineering concepts.
Jayesh Chaudhari
Assistant Manager, Jio
"Helped me level up my career"
The practical skills I gained here helped me transition into better opportunities and work on more impactful systems.
Akhil Giri
Software Engineer, Kyndryl
"From concepts to real AI systems"
Anuj's lectures go beyond theory, I was able to apply LLM fundamentals and RAG concepts directly in my workflow after building the Lovable clone project here.
Sahil Naik
Software Developer, Oracle
"Confidence to build production-grade systems"
This program built real confidence in backend fundamentals and system design. I can now design AI-powered systems instead of just consuming APIs.
Satyansh Shukla
Lead Software Engineer, Accolite
"Well-structured from basics to advanced"
The course is exceptionally well-structured and comprehensive, blending foundational concepts with advanced material for a thorough grasp.
Roshan Kumar
Software Engineer, PwC
"Worth it for real-world AI skills"
A bit pricey, but completely worth it. The ability to build production-ready AI systems and not just demos made all the difference.
Vatsal Adhiya
SDE Intern, Texas Instruments
"Projects that feel like real products"
Building weekly projects, including a Lovable-style clone, helped me understand how real AI products are structured and shipped.
Jyoti Bharti
Software Engineer, Johnson Controls
"Well-structured with real examples"
The course is well-structured and packed with real examples. What sets it apart is the focus on actual applications rather than just theory.
Rahul Kumar
Software Engineer, BPCE NATIXIS
"Built and shipped a real AI project"
This course helped me build a production-grade Lovable clone AI application from scratch, something I could confidently showcase at work.
Touhid Sayed
Senior Analyst, Capgemini
"Hands-on, not just theory"
Unlike courses that stay broad and theoretical, this one is practical and project-based, with an engaging style built around real projects.
Abhigyan
Software Engineer, OneTrust
"Strong fundamentals + real support"
The program builds strong backend and system design fundamentals, and the support system ensures you never get stuck.
Arunima Saxena
Senior Software Test Analyst, Accenture
"Clear path to applying AI in work"
The structured approach made it easy to apply AI concepts in real-world scenarios, especially in building scalable systems.
Abhishek Suvarnakar
Software Development Engineer, Equilend
"Perfect for beginners like me"
This course is perfect for beginners struggling to get started. Well-structured, covers the essentials, with live weekend classes too.
Anandini Tripathy
Product Engineer, Cummins
"Consistency that compounds skills"
Weekly assignments and system-building exercises helped me truly internalize backend and AI engineering concepts.
Jayesh Chaudhari
Assistant Manager, Jio
"Production-grade thinking, not tutorials"
The course teaches how to think like an engineer building production systems, not just follow along tutorials.
Aiman Shakeel
Senior Software Engineer, Cognizant
"Helped me level up my career"
The practical skills I gained here helped me transition into better opportunities and work on more impactful systems.
Akhil Giri
Software Engineer, Kyndryl
"Hands-on learning that sticks"
Implementing concepts like RAG and system design while coding made everything click and stay long-term. Anuj explains concepts while implementing them in code, a hands-on approach that makes real-world development easier to grasp.
Aanshi Vishwakarma
Lead Engineer, HCLTech
faq
Frequently Asked Questions
General Questions
This cohort is ideal for software engineers, backend developers, full-stack developers, QA, support roles, and other working professionals who want to build AI products or transition into AI Engineering roles. Basic programming experience in any language is recommended.
The cohort runs live over 10 weeks. You'll build a production-grade AI Operating System on top of a real, pre-built enterprise application, alongside your instructor and mentors, asking questions in real time and getting guidance throughout.
Live classes are conducted every Saturday and Sunday at 8:00 PM IST. Each session covers fundamentals and theory, hands-on implementation, architecture discussions, AI-assisted development workflows, and doubt-solving.
Around 6–7 hours per week, roughly 5 hours for the two live weekend sessions, plus 1–2 hours of self-study or practice during the week.
Prerequisites & Fit
Program & Curriculum
Teaching & Mentorship
Certification & Access
Pricing & Refunds
Career Outcomes & Community
the opportunity is now
The Best Career Investment You'll Ever Make
AI roles are growing faster than talent can keep up. In 10 weeks, you could be ready to step into one.