Stop Watching Tutorials. Start Building Real AI Systems.
Everyone's talking about AI agents — but most tutorials stop at "Hello World" chatbots. The real challenge? Building systems that actually work in production, connect to real tools, and solve enterprise problems.
This cohort fixes that. In 6 weeks and 12 hands-on sessions, you'll go from zero to building production-ready agentic AI systems — from single agents to multi-agent orchestration, RAG pipelines, and deployment governance. Every session ends with something you can show in an interview or deploy at work.
Ankita is a Data Engineer who's helped 1,050+ professionals on Topmate with interview prep, career guidance, and data engineering resources. Her best-selling resources have been purchased by hundreds of engineers. This isn't academic theory — it's a practitioner's guide to the most in-demand AI skills of 2026.
What You'll Walk Away With
Build AI Agents from Scratch
Design, build, and deploy intelligent agents using LangChain, AutoGen, and OpenAI/Azure frameworks
Real System Integrations
Connect agents to databases, APIs, Slack, email, and enterprise tools using tool calling
RAG & Vector Databases
Build intelligent search and retrieval systems that ground AI responses in real data
Multi-Agent Orchestration
Design systems where multiple AI agents collaborate, delegate tasks, and solve complex problems
Production Deployment
Deploy agents with governance, cost control, observability, and enterprise-grade reliability
Interview-Ready Portfolio
A capstone project, GitHub portfolio, and system design skills for Agentic AI roles
Who This Cohort Is For
Software Engineers
Developers who want to add AI agent skills to their toolkit and build production-ready systems.
Data Engineers & Scientists
Data professionals looking to expand into the agentic AI space and build intelligent pipelines.
Career Transitioners
Professionals from any tech background wanting to break into AI/ML engineering roles.
AI Enthusiasts
Anyone with basic programming skills who wants to go beyond ChatGPT and build real AI systems.
This is NOT for you if:
- You want a passive, watch-only course — this is hands-on, build-every-session
- You expect to learn everything without coding — basic programming is helpful
- You're looking for just theory and slides — every session produces a working system
Reviews from Real Clients
"Ankita's Data Engineering Interview Preparation Plan was the best investment I made. It covered every topic in the right depth — from SQL to system design to real scenario questions. I felt genuinely prepared walking into my interviews and landed offers from two companies."
"The Interview Safarnama resource is incredible — real questions from real interviews, organized by topic and difficulty. It gave me the confidence to tackle even the toughest system design rounds."
"Ankita's guidance helped me transition from a backend role to data engineering. She was practical, specific, and gave me a clear roadmap instead of generic advice. Her production scenarios resource was a game changer."
"The mock interview package was exactly what I needed. Ankita's feedback was honest and actionable — she pointed out gaps I didn't even know I had. After 10 sessions, I was a completely different candidate."
"The 'When Theory Ends' resource bridged the gap between what I learned in courses and what companies actually ask. Real production problems with real solutions — this is what senior interviews are about."
Based on 1,050+ bookings across interview prep, career guidance, and resources on Topmate
6 Weeks · 12 Hands-On Sessions
Goal: Understand what AI agents are and build your first working agent from scratch.
- What makes an agent different from a chatbot — autonomy, reasoning, and tool use
- Core agent architecture: perception, planning, action, memory
- Hands-on: Build a functional AI agent using LangChain/OpenAI
- Understanding prompts, chains, and agent loops
Goal: Make agents useful by connecting them to databases, APIs, and external tools.
- Tool calling — how agents interact with external systems
- Connecting to databases, REST APIs, Slack, and email
- Building custom tools and function definitions
- Error handling and retry logic for real-world reliability
Goal: Design agents that automate workflows and monitor systems proactively.
- Event-driven agent architectures for automation
- Monitoring agents: health checks, alerting, and anomaly detection
- Workflow automation patterns and scheduling
- Building agents that observe, decide, and act autonomously
Goal: Build RAG systems that ground AI agents in real, accurate data.
- Retrieval-Augmented Generation (RAG) architecture end-to-end
- Vector databases — embeddings, indexing, and similarity search
- Chunking strategies, retrieval quality, and re-ranking
- Building a knowledge-grounded agent that answers from your own data
Goal: Design the architecture for your capstone project with guided feedback.
- Choose your capstone: Customer Support Bot, Resume Optimizer, Portfolio Builder, IT Automation, or Procurement Agent
- System design workshop — whiteboard your agent architecture
- Define tools, data sources, agent roles, and interaction flows
- Peer review and instructor feedback on your design
Goal: Build systems where multiple AI agents work together to solve complex problems.
- Multi-agent orchestration patterns — delegation, collaboration, supervision
- Agent-to-agent communication and shared memory
- Using AutoGen and crew-style frameworks for multi-agent setups
- Real-world use case: a team of agents that research, draft, and review
Goal: Build agents that evaluate quality, extract insights, and improve over time.
- Agent self-evaluation and output scoring
- Building critic agents that review and improve other agents' work
- Data extraction and insight generation pipelines
- Feedback loops and continuous improvement patterns
Goal: Deploy agents to production with enterprise-grade reliability and governance.
- Containerization and deployment strategies for AI agents
- Cost control — token budgets, caching, and rate limiting
- Observability: logging, tracing, and monitoring agent behaviour
- Governance frameworks: guardrails, safety, and access controls
Goal: Build your capstone project and optimize it for performance and reliability.
- Guided build session — implement your capstone architecture
- Debugging and optimization with live instructor support
- Performance tuning: latency, cost, and accuracy trade-offs
- Peer code reviews and feedback sessions
Goal: Position yourself for the hottest AI roles — resume, LinkedIn, and portfolio strategy.
- Target roles: AI Engineer, GenAI Engineer, Agentic AI Engineer, ML Engineer, AI Architect
- Resume rewriting for AI roles — what hiring managers actually look for
- LinkedIn and GitHub portfolio optimization
- Building a compelling narrative around your agentic AI projects
Goal: Ace system design interviews for AI/ML engineering roles.
- System design interview framework for AI-heavy roles
- Designing agent architectures on a whiteboard under time pressure
- Common system design questions: RAG systems, recommendation engines, multi-agent platforms
- Mock interview practice with real-time feedback
Goal: Present your capstone, get feedback, and simulate a real hiring experience.
- Demo Day — present your capstone project to the cohort and invited reviewers
- Hiring simulation: mock technical interviews based on your capstone
- Feedback and scoring from Ankita and peer reviewers
- Graduation: career roadmap, continued learning resources, and community access
Meet Ankita Gulati
Ankita Gulati is a Data Engineer who turns raw data into valuable insights and has a passion for helping aspiring tech professionals land their dream roles. Having recently conquered the interview gauntlet herself, she understands the highs, lows, and what actually works.
Her resources on Topmate have been purchased by 1,050+ professionals — from the best-selling Data Engineering Interview Preparation Plan (363 purchases) to Interview Safarnama (380 purchases) and the acclaimed "When Theory Ends: Production Scenarios" guide. She blends technical depth with practical, interview-tested advice.
In this cohort, Ankita brings the same hands-on, no-fluff approach — every session produces a working system, every concept is grounded in real production use cases, and career positioning is baked into the curriculum from day one.
What's Included
12 Live Sessions
Saturdays & Sundays · 2 hours each · Hands-on, build-every-session format.
Lifetime Recording Access
All session recordings available forever — revisit any session whenever you need it.
Architecture Templates
Production-ready templates for agent architectures, RAG systems, and multi-agent setups.
Prompt Template Library
Curated prompt templates for different agent types, tool calling, and evaluation.
Resume & Interview Toolkit
Resume templates, LinkedIn optimization guide, and interview prep framework for AI roles.
Private Community
Cohort community for peer support, project collaboration, job leads, and networking.
Capstone Project Options
Choose one capstone or bring your own idea — you'll design, build, and demo it by the end of the cohort.
Roles You'll Be Ready For
The most in-demand AI roles of 2026 — and this cohort gives you the portfolio to land them.
Frequently Asked Questions
No prior AI/ML experience is required. Basic programming knowledge is helpful but not mandatory. The cohort starts from fundamentals and builds up to advanced topics — you'll learn everything you need along the way.
Primarily Python, along with frameworks like LangChain, AutoGen, and OpenAI/Azure SDKs. We'll also work with vector databases, APIs, and deployment tools. All code templates and starter projects are provided.
12 sessions over 6 weeks — Saturdays and Sundays, starting April 25, 2026. Each session is 2 hours (10 AM IST). Plus 3–5 hours per week for assignments and capstone work. Everything is hands-on and directly contributes to your portfolio.
Yes — you get lifetime access to all session recordings. But we strongly recommend attending live for the hands-on coding, real-time debugging help, and Ankita's direct feedback on your projects.
The cohort is specifically designed with career outcomes in mind. Sessions 10–12 cover career positioning, system design interviews, and a hiring simulation. You'll graduate with a portfolio project, optimized resume, and interview preparation — everything you need to land an Agentic AI role.
Absolutely! Request a callback or send a WhatsApp message. We'll help you understand if this cohort is the right fit for your background and career goals. No pressure — just an honest conversation.