Transformative GenAI Domain-specific Track
Flagship Machine Learning Program
PwC India x IK Agentic AI Career Accelerator
Interview Preparation Domain-specific Track
Data Engineers aspiring to master Agentic AI skills
14 weeks
60+ hours of live interaction with industry experts from top tech companies
30+ hours of expert-guided live hands-on projects
21+ hours of power-packed specialized sessions
3 Guided Projects, 3 Capstone Projects to choose from
Generative & Agentic AI practitioners from FAANG and other global Tier 1 companies
Autonomous AI Agents, Multi-Agent Systems, Agentic AI Strategies, RAG, LLM Orchestration, real-world application of Agentic AI, and more
Gain practical insights from top engineers at FAANG+ companies who’ve built large-scale AI/ML data pipelines and production systems.
Master the modern GenAI data stack and orchestration workflows through a step-by-step curriculum tailored for your profile.
Designed to help full-time professionals upskill without affecting your job or personal schedule.
Focus on AI-driven data infrastructure, intelligent pipeline automation, Spark ML, Kafka, Airflow, and Hugging Face tools
Build and deploy multi-agent systems like AI anomaly detectors, intelligent ETL generators, and scalable data processing pipelines—reviewed by FAANG+ mentors.
With an NPS of 55 and an average learner rating of 4.75+, our structured, hands-on approach consistently earns high praise from tech professionals like you.
Enhance call center operations with a voice-activated chatbot powered by Generative AI. Process audio inputs and generate context-aware responses for seamless customer engagement. Features include multilingual support, sentiment analysis, and conversation memory. Integrate Whisper, OpenAI GPT, and LangChain. Use FFmpeg for audio processing and build UIs with Streamlit and Gradio.
Build an intelligent healthcare assistant with LangGraph for structured reasoning and medical knowledge integration. This agent handles patient queries, symptom assessment, and information retrieval through conversation. It features contextual memory, appointment scheduling, medication reminders, and personalized advice. Utilize LangGraph for decision trees, RAG for medical knowledge retrieval, and Streamlit for the interface. Tools include Python, LangGraph, Pinecone, and OpenAI APIs.
Develop a financial advisory system using LangGraph’s multi-agent architecture. Implement specialized agents for market analysis, portfolio management, risk assessment, and recommendations that work collaboratively. Use agent-to-agent communication, parallel tasks, and consensus mechanisms alongside ReAct and Chain-of-Thought prompting for transparent reasoning. Features include data visualization, investment strategies, and scenario planning. Build with LangGraph for orchestration, LangChain for tools, ChromaDB for vector storage, and Streamlit for dashboards.
Design and build an AI-powered Anomaly Assistant that:Detects, explains, and optionally resolves anomalies in data pipelines by combining Retrieval-Augmented Generation (RAG) with Agentic AI capabilities.
Build an Intelligent ETL Code Generator that helps data teams automatically translate natural language business requirements into production-ready ETL code, reducing development time from weeks to hours while ensuring consistent quality and comprehensive testing.
Work on personal or professional projects of your choice. BYOP offers mentorship, structured guidance, and feedback to ensure projects are aligned with industry standards and best practices. It fosters creativity, innovation, and real-world problem-solving, enabling participants to build impactful solutions. You will receive guidance on selecting the right tools and frameworks based on project requirements.
+ Instructors to Train You
FAQs
Do I need prior experience in AI or ML to take this course?
No prior knowledge of AI or ML is needed. As long as you have a strong background in data engineering and are comfortable with Python or similar languages, you’ll be able to keep pace. The course starts with fundamentals and progressively builds toward advanced agentic systems.
How is this different from other AI or ML programs?
This isn’t a generic AI bootcamp or prompt engineering course. It’s purpose-built for data engineers who want to build production-grade agentic pipelines and workflows, aligned with FAANG+ expectations, using real-world tools and deployment architectures.
What kind of projects will I work on?
You’ll develop hands-on projects like AI-driven anomaly detectors, intelligent ETL pipeline generators, and a capstone of your choice, such as a data compliance checker or fraud detection agent. All projects are built for real-world use and strengthen your AI portfolio.
Can I bring a personal or work project into the program?
Yes. You can opt for a BYOP (Bring Your Own Project) track, where you’ll get expert feedback from mentors to refine and deploy your own project, ensuring it meets production standards.
What are the real-world applications of Agentic AI?
Agentic AI is already powering innovation across industries:
In robotics: autonomous decision-making and control
What exactly is Agentic AI, and how is it different?
Agentic AI refers to systems that proactively reason, decide, and act toward defined goals using LLMs and external tools. Unlike traditional AI, which follows direct commands, agentic systems adapt on the fly, coordinate tasks, and self-correct without constant input.
How do capstone projects help in career growth?
These projects are designed with input from FAANG+ hiring managers. Each one highlights your applied AI skills—something 67% of recruiters now value over certifications. They’re reviewed for scalability, relevance, and impact, making your portfolio job-ready.
How will this course support my FAANG+ transition?
This course equips you with in-demand Agentic AI skills that are becoming essential in top-tier data engineering roles. Pairing it with our 8–12 week Interview Lab gives you access to expert-tailored coaching, mock interviews, and placement support to prepare for coveted roles at MAANG+ companies.
What tools and frameworks will I gain hands-on experience with?
You’ll work with LangChain, LangGraph, CrewAI, LlamaIndex, Streamlit, Kafka, Spark, Airflow for GenAI, Hugging Face, Docker, Pinecone, and more—learning how to integrate them into scalable agentic data systems.
Who are the instructors?
All instructors are current or former engineers from FAANG+ and Tier-1 companies. They’ve built large-scale AI/ML and data platforms and bring deep insight into applied agentic workflows.
What’s the weekly time commitment?
Expect to spend around 8 hours per week on live classes, project work, and assignments. Across 14 weeks, you’ll engage in 60+ hours of live instruction, 30+ hours of guided projects, and 21+ hours of role-specific sessions.
Is the course live or self-paced?
It follows a hybrid format. Core content and projects are taught live every week, while self-paced bonus content and career prep modules support flexible schedules.
What if I miss a live class?
No worries. Every live session is recorded and made available on demand, so you can catch up anytime or revisit concepts during project work or interview prep.
Are financing options available?
Yes, we offer flexible payment plans and financing options to make the program accessible to working professionals in India.
25,000+ Professionals Trained
₹23 LPA Average Hike
600+ MAANG+ Instructors
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Join 25,000+ tech professionals who’ve accelerated their careers with cutting-edge AI skills
25,000+ Professionals Trained
₹23 LPA Average Hike 60% Average Hike
600+ MAANG+ Instructors
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Time Zone: Asia/Kolkata
Hands-on AI/ML learning + interview prep to help you win
Time Zone: Asia/Kolkata
Hands-on AI/ML learning + interview prep to help you win
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