Now Enrolling — Limited Seats
NUVIQ

From Service Company to
MAANG AI Engineer
in 12 Weeks

India's most intensive AI & GenAI program. 36 sessions. 72 hours. 3 real projects. Built for working professionals who want real results.

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Engineers Placed
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Avg. Salary Hike
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Placement Rate
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Program Duration
Where Our Engineers Work
Google
Microsoft
Meta
Amazon
NVIDIA
OpenAI
Anthropic
Adobe
Flipkart
Uber
Databricks
DeepMind
The AI Revolution

The Disruption Timeline
Is Accelerating

Every 6 months, a new frontier model ships. Engineers who don't adapt get left behind.

2023
GPT-4 & Foundation Models
175B-parameter models go mainstream. GitHub Copilot automates 46% of code. Transformer architecture becomes required knowledge for every SWE interview.
2024
Claude 3.5, Gemini 1.5 & RAG Pipelines
Million-token context windows arrive. Companies deploy RAG + vector DB architectures. LangChain and LlamaIndex become must-know frameworks.
2025
Cursor, Devin & Agentic AI
Multi-agent orchestration goes production. Fine-tuning with LoRA/QLoRA becomes table stakes. Companies cut traditional SWE hiring by 15% while AI engineer demand surges +67%.
2026 — You Are Here
GPT-5, Claude 4 & Autonomous Agents
Frontier models reason across 10M+ token contexts. AI agents chain tools, write code, and deploy themselves. The dividing line: engineers who build AI systems vs. those replaced by them.
2028
AI-Native Software Engineering
ML system design, prompt engineering, and model evaluation are core competencies. Traditional SWE without AI fluency? Obsolete. The transformation is complete.
$184B
Global AI Market
37%
CAGR Growth
300K+
AI Jobs in India
+67%
AI Job Growth YoY
The System

The 12-Week AI
Career Transformation

36 live sessions. 72 hours. 3 real projects. Every week builds on the last.

01
MONTH 01 · WEEKS 1–4
Foundations & Core AI
Python for AINumPy & PandasData VisualizationML FoundationsRegression & ClassificationNeural NetworksBackpropagationPyTorch & TensorFlowCNNsNLP BasicsRNNs & LSTMsAttention MechanismSentiment Analysis
✓Build your first ML model from scratch. Create a Smart Content Assistant. AI/ML Certification.
02
MONTH 02 · WEEKS 5–8
GenAI & LLMs
TransformersSelf-AttentionGPT, BERT, LLaMATokenization (BPE)Prompt EngineeringChain-of-ThoughtReActOpenAI & Claude APIRAG SystemsVector DBs (Pinecone, ChromaDB, FAISS)Fine-tuning (LoRA, QLoRA)
✓Build a production Document Q&A System with a full RAG pipeline. GenAI Certification.
03
MONTH 03 · WEEKS 9–12
Production & Deployment
AI AgentsLangChainLlamaIndexCrewAIMulti-Agent SystemsMLOpsAWS SageMakerAzure MLDockerCI/CD for MLScaling & CachingAI Security & GuardrailsCapstone Project
✓Build a Multi-Agent Research Analyst + end-to-end capstone. Production AI Certification. Career Sprint begins.
04
CAREER SPRINT + PLACEMENT · ONGOING
Placement & Referral
Resume OptimizationLinkedIn UpgradeMock Interviews1:1 Career CoachingMAANG Engineer MentorsDirect ReferralsSalary NegotiationOffer EvaluationPersonal Branding
✓Direct referrals to 50+ partner companies including Google, Microsoft, Amazon, Meta. 98% placement rate. Support continues until you're placed.

What You'll Actually Build

Not toy demos. 3 production projects + 1 capstone that make MAANG recruiters call you back.

PROJECT 01
Smart Content Assistant
Build an end-to-end AI application combining ML and NLP into a production-grade tool. Covers text preprocessing, sentiment analysis, named entity recognition, and integrates classification models into a fully functional content assistant.
PythonPyTorchNLPHugging FaceFastAPI
PROJECT 02
Document Q&A System
Build a full RAG pipeline that retrieves from thousands of documents using vector databases, implements hybrid search with embeddings, chains prompts with LLMs, and delivers accurate answers with source citations. Includes fine-tuning with LoRA/QLoRA.
LangChainPineconeChromaDBOpenAI APIFAISS
PROJECT 03
Multi-Agent Research Analyst
Orchestrate an autonomous AI system with multiple specialized agents that collaborate to research, analyze, and report. Implements ReAct reasoning, tool calling, memory, and self-correction loops. Deployed to cloud with monitoring and scaling.
CrewAILlamaIndexClaude APIDockerAWS
CAPSTONE
End-to-End Portfolio Project
Combine every skill from the 12-week journey into one comprehensive, production-grade AI project. Design, build, deploy, and present a complete system that demonstrates mastery across ML, GenAI, agents, and cloud deployment — your ultimate portfolio piece for interviews.
Full Stack AISystem DesignCloud DeployMLOpsPortfolio Ready
Your Toolkit

The AI Stack You'll Master

🐍 Python
🔥 PyTorch
🤗 Hugging Face
🦜 LangChain
🦙 LlamaIndex
🧠 OpenAI API
🔮 Claude API
📌 Pinecone
🌊 Weaviate
⚡ FastAPI
🐳 Docker
☸️ Kubernetes
📊 MLflow
📈 Weights & Biases
🔬 FAISS
🚀 vLLM
⚙️ TorchServe
☁️ AWS SageMaker
PJ
Prateek Jain
Founder & CEO, Nuviq · Ex-Google AI
"I sat in Google's office and watched them reject 40 brilliant engineers in one week. Not because they weren't smart enough. Because nobody taught them how to think in embeddings, reason about attention heads, or design ML systems at scale. I quit Google to fix that."
IIIT Hyderabad (CS)IIM Gold MedallistEx-Google AI PlatformBuilt ML infra serving 1B+ requests/day1000+ Engineers Placed at MAANGGuest Lecturer, IIT Delhi
Real Transformations

1200+ Engineers.
Same Results.

All verifiable on LinkedIn. Every result is documented.

TCS → Microsoft · ML Engineer
"The Transformer implementation from scratch completely changed how I think about attention. My Microsoft interviewer said my ML system design answer was 'the best he'd seen in 6 months.' I owe that to Prateek's mock interviews."
Rohan M.+240%
Wipro → Amazon · Applied Scientist
"₹2,999 trial turned into a ₹32 LPA role as Applied Scientist. The RAG pipeline project I built during Month 2 became my interview talking point. The interviewer asked me to whiteboard my Pinecone indexing strategy — I nailed it."
Priya N.+210%
Infosys → Google · AI Platform
"The ML system design module is what got me in. I designed a real-time recommendation system at scale during my Google interview — two-tower architecture, ANN retrieval, feature store, the works. They said 'You clearly think like a Google engineer.'"
Arnav S.+280%
HCL → NVIDIA · Deep Learning
"I thought NVIDIA was impossible for someone from HCL. But the PyTorch fundamentals and distributed training knowledge I gained made me stand out. My fine-tuning project using QLoRA on Llama was the portfolio piece that clinched it."
Sneha K.+190%
Startup → Meta · GenAI Team
"3 offers in 2 weeks: Meta, Databricks, and Adobe. The multi-agent project I built with LangChain was on my GitHub — every interviewer asked about it. The alumni network is insane. Batch 4 senior referred me directly to the hiring manager."
Vikram R.+320%
TCS → NVIDIA · ML Infrastructure
"My wife convinced me to stop overthinking. 4 months later, NVIDIA at ₹42 LPA. The vLLM deployment and model serving module gave me the exact skills their team needed. Old TCS salary: ₹11 LPA. She still takes credit."
Batch 6 Student+282%
The Difference

Why Nuviq Works When
Everything Else Fails

🎓
MAANG Instructors, Not YouTubers
Staff engineers from Google and Microsoft who actually hire AI engineers teach you what gets you hired.
🔧
Real AI, Not Toy Projects
Production-grade RAG systems. Fine-tuned LLMs. Deployed ML pipelines. Real projects that make recruiters stop scrolling.
🎯
50+ Mock Interviews
With actual MAANG interviewers. ML system design practice. We drill it until you can't fail.
✅
Guaranteed Placement
98% placement rate. If we can't place you, we lose money. Our incentives are perfectly aligned with yours.
💰
Pay After You Land
60% of fees payable only after placement. We eat the risk. Every other program takes your money upfront.
🤝
1200+ Alumni Network
Your classmates are at Google, Microsoft, Amazon. They refer you. 42% of placements come from alumni referrals.
Credentials

Walk Out With 4
Industry Certifications

Recruiters filter LinkedIn for these. Without them, you're invisible.

01
Google Professional ML Engineer
The gold standard. Only 12% of AI candidates have this.
02
AWS Machine Learning Specialty
Amazon runs 40% of cloud AI. This cert increases callbacks by 47%.
03
Microsoft Azure AI Engineer
65% of Fortune 500 use Azure. Deploy AI at enterprise scale.
04
DeepLearning.AI Specialization
Andrew Ng's stamp of approval. The most recognized AI credential.
Zero Risk

You Literally Cannot Lose

Four layers of protection. We put our money where our mouth is.

1
60% Pay-After-Placement
The majority of the fee is payable only after you get placed.
2
Guaranteed Placement
We don't stop until you have an offer letter. 98% placement rate.
3
Lifetime Curriculum Access
AI changes fast. Your education keeps up. New models? Updated modules. Free forever.
4
1200+ Alumni Network
Access to engineers at Google, Microsoft, Amazon, Meta, NVIDIA.
Average salary hike: 240% · 98% placement rate

3,400% Return
On Investment

Your first month's salary hike pays for the entire program. Our alumni have gone from service companies to MAANG roles with 2–3x salary jumps. 1200+ engineers placed. The highest-ROI investment in your career.

Pay After Placement
60% of fee only after you land a job
Chat with AI Expert

In 2028, there will be two types of engineers: those who build AI, and those replaced by it. The best time to learn AI was 2023. The second best time is today.