Zero to Databricks Expert — Complete Bundle | GeekCoders
NEW: Now includes Agentic AI Bootcamp

The most complete
Databricks program
ever built.

4 courses bundled into one. Databricks Foundation, 4 production pipeline projects, 4 end-to-end AI agents, and 50 PySpark interview questions — everything you need to go from 8 LPA → 30+ LPA with real work to show.

Lifetime access 4 courses bundled 8 projects + 50 Qs
databricks_bundle.yaml
# zero to expert — complete bundle
course_1: Interview Ready Program
   projects:
    - medallion_pipeline    # Delta · UC
    - dlt_mlflow_workflow   # DLT · MLflow
    - genai_resume_screen  # RAG · LLM
    - production_ai_agent  # Mosaic AI
course_2: Agentic AI Bootcamp
   agents:
    - data_analyst_agent      # SQL · UC
    - doc_rag_agent           # Vector
    - workflow_orchestrator   # LangGraph
    - production_deploy_agent  # Mosaic
course_3: 50 PySpark Questions
interview_qs: 50
access: lifetime
₹25,000 9,999
4 COURSES BUNDLED
4+4
Production builds
6,000+
Students
30+ LPA
Target roles
Lifetime
Access + updates
// the hard truth

What nobody tells you about Databricks salaries

Fintech, healthcare, retail, AI-first teams running Databricks at scale pay packages that make your current salary look like an internship — but they don't hire from courses that teach DataFrames and call it data engineering.

Mid-level DE
₹30 LPA
3–5 yrs · the minimum bar

Owns Delta Lake pipelines, Unity Catalog and DLT in production. This is the floor, not the ceiling.

Senior DE
₹40 LPA
5–8 yrs · product companies

Leads Medallion architecture, MLflow workflows, owns model serving end-to-end.

Lead / GenAI DE
₹50 LPA+
rare · ridiculously well-paid

Owns Vector Search, RAG agents, Mosaic AI deployments and production AI agent systems — the skills almost nobody has yet.

// the gap

Most courses teach theory. So when the interviewer says "walk me through a GenAI agent pipeline on Databricks" — you freeze.

You can explain what a DataFrame is. You've heard of Delta Lake. You've watched a Spark optimization playlist.

But the interviewer doesn't want theory. They want to know how you'd design ingestion with Auto Loader, handle late-arriving data, recover a DLT pipeline from a schema change, ground a RAG agent against Unity Catalog tables, and deploy an agentic workflow with LangGraph and Mosaic AI.

That gap — from theory to production-grade agents — is exactly what this bundle closes.

Most tutorials give you

  • 50-line DataFrame demos
  • "Hello world" Delta tables
  • Disconnected feature walkthroughs
  • Zero agentic AI coverage
  • No production architecture

This bundle gives you

  • 4 end-to-end pipeline projects
  • 4 production AI agent builds
  • LangGraph · Mosaic AI · Agent Bricks
  • 50 solved PySpark interview Qs
  • Real CI/CD with Asset Bundles
// 8 production builds

Two complete tracks. Zero fluff.

Every build is an end-to-end, deployable system — not a demo. Ship it to GitHub, walk through it in interviews, use it at work from day one.

Track 1 — Interview Ready Program · 4 Pipeline Projects
01
Project One
PySpark · Delta · Unity Catalog

Production Medallion Pipeline

A real Bronze → Silver → Gold architecture with Auto Loader streaming ingestion, schema enforcement, Unity Catalog governance and Z-ordering. The exact pattern enterprise teams ship.

PySpark Delta Lake Unity Catalog Auto Loader
02
Project Two
DLT · MLflow · Model Serving

DLT + MLflow End-to-End Workflow

Declarative Delta Live Tables with expectations, quality rules and auto-scaling. Train, track and register models with MLflow, then serve them at low-latency endpoints. The full MLOps loop.

Delta Live Tables MLflow Model Serving
03
Project Three
LLMs · Vector Search · RAG

GenAI Resume Screening System

Ingest resumes, extract structured data with LLMs, embed with Vector Search, score candidates against job descriptions using RAG grounding. Deploy as a Databricks App recruiters actually use.

LLM Parsing Vector Search RAG Databricks Apps
04
Project Four
AI Agents · Mosaic AI · Agent Bricks

Production AI Agent on Databricks

Build an agentic system with the Mosaic AI Agent Framework, Agent Bricks and Unity Catalog Functions. The agent reads real tables, calls tools and reasons — the highest-paid GenAI skill in 2026.

Agent Bricks Mosaic AI UC Functions
Track 2 — Agentic AI Bootcamp · 4 Production Agents
A1
Agent One
Mosaic AI · UC Functions · SQL

Data Dictionary App on Unity Catalog

A production Databricks App + MCP server that auto-reads Unity Catalog schemas, generates rich column-level documentation with LLMs, and serves it through a chat interface. The governance tool every data team needs — and almost nobody has.

Unity Catalog MCP Server Databricks Apps Mosaic AI
A2
Agent Two
Vector Search · Embeddings · RAG

Resume and JD Matcher System

Parse resumes with LLMs, embed both resumes and job descriptions into Databricks Vector Search, then use a LangGraph agent with UC Functions to score, rank and explain candidate-to-JD fit. A real recruiting-tech build, end to end.

Vector Search LangGraph RAG Scoring UC Functions
A3
Agent Three
LangGraph · Multi-Tool · Orchestration

Hospital Agent

A real healthcare prior-authorization agent — Streamlit Databricks App + MCP server + LangGraph orchestration. The agent pulls patient context from UC tables, checks clinical guidelines, drafts approvals and escalates edge cases. A high-stakes, regulated-industry build.

LangGraph MCP Server Healthcare Streamlit App
A4
Agent Four
Mosaic AI · Serving · Agent Bricks

Support Ticket Triage

An agent that classifies incoming support tickets, assigns priority and routes to the right team using historical resolution data, then drafts a first-response message. Includes MLflow evaluation, human-in-the-loop review and Mosaic AI serving — production grade end to end.

Classification Tool Calling MLflow Eval HITL
// also included

50 PySpark Interview Questions — solved end-to-end

Real MNC coding problems across 10 focus areas — every single question comes with a detailed explanation, a working PySpark notebook solution, and the concept behind the answer.

PySpark Fundamentals
Joins & Aggregations
Window Functions
Performance & Skew
UDFs & pandas UDFs
Streaming & Delta Lake
PySpark
Practice · Interview Prep

50 PySpark Questions

10 categories · every Q with working notebook solution · 5,000+ students already passed their interviews with these

50
Questions
10
Categories
5★
Rated
// 15+ industry tools

Master the complete 2026 Databricks stack

Every tool across pipelines, ML, AI agents and interview prep — taught the way enterprise teams actually use them.

Databricks Lakehouse
PySpark
Delta Lake
Unity Catalog
MLflow
Vector Search
LLMs & RAG
LangGraph
AI Agents
Agent Bricks
// everything included

What you get when you enroll today

Databricks Foundation

Spark architecture, PySpark, Delta Lake, Unity Catalog, DLT — every fundamental enterprise teams expect.

4 Production Pipeline Projects

Medallion, DLT+MLflow, GenAI Resume Screening, and Production AI Agent — real codebases you can deploy and showcase.

4 Agentic AI Builds

Data Analyst Agent, Document RAG Agent, Workflow Orchestrator, and Production Deployment — the complete agentic skill set.

50 PySpark Interview Questions

Real MNC coding problems — joins, windows, optimization, skew handling, streaming — solved end-to-end in notebooks.

Mentor Guidance

Direct access to Sagar for blockers. Code reviews, architecture feedback and career guidance when you're stuck.

Lifetime Access + Community

Re-watch any module. Every future update included. Private community of 6,000+ Databricks engineers.

Sagar Prajapati
// taught by

Sagar Prajapati

Founder, GeekCoders · Founding Member, LakeFusion

Founder of GeekCoders and a founding member of LakeFusion (Databricks-native SaaS). 6,000+ students mentored. Databricks Certified. He teaches exactly what he ships in production — including the agentic AI systems he's building at LakeFusion right now.

6K+
Students
80K+
Followers
500+
Alumni in MNCs
// real transformations

6,000+ engineers have already made the jump

They finished the projects, cleared interviews, and moved into Databricks roles. LinkedIn verified.

Deloitte
Accenture
Microsoft
Amazon
Fractal
EXL
Persistent.
★★★★★

I had pipeline experience in India but struggled to explain end-to-end design in interviews. After Sagar's project track I could walk through ADF → Databricks → serving with real examples. That landed me a Lead DE role in the UAE.

India → UAE Lead DE role
Manish AcharyaMA
Manish Acharya
Lead Data Engineer · UAE
★★★★★

I knew individual tools but couldn't connect them in one architecture. The end-to-end project forced me to implement ingestion, transformation and reporting together — exactly what LSE interviewers asked about. It finally clicked as one system.

Cleared interviews with a full project story
Toshita ChakrabortyTC
Toshita Chakraborty
Data Engineer · London Stock Exchange
★★★★★

Our team started pitching GenAI to clients and I was behind on Vector Search and LLM patterns. Sagar's modules are paced for working engineers — notebook-first, no fluff. I applied RAG and embeddings on client work within weeks.

Moved into GenAI work at EXL
Arushi GuptaAG
Arushi Gupta
Data Engineer · EXL
★★★★★

I'd used ADF and Databricks separately on paper, but froze when asked how they connect in one production flow. Sagar's live build showed error handling, incremental loads and hand-offs — the detail service companies expect from mid-level engineers.

Production pipeline confidence
Surajit MetyaSM
Surajit Metya
Data Engineer · Latent View
★★★★★

I've bought multiple project courses here. Nothing is recycled theory — every module maps to something we actually deploy for clients. As a Project Lead, I point junior engineers here when they need Databricks depth fast.

Recommends GeekCoders to his team
Mahesh GaneMG
Mahesh Gane
Project Lead · Persistent Systems
// your turn

You could be the next one.

Same 8 builds. Same mentor. Same WhatsApp community of 6,000+ engineers.

Join them · ₹9,999
// included with enrollment

Bonuses that come free with your seat

Real assets. Not "value-stacked" filler. Use them from day one.

BONUS 01

Lifetime Access to All 4 Courses

Re-watch any lesson across all courses. Every future update to every course included — forever.

BONUS 02

Databricks Interview Prep Kit

Real questions from MNC technical interviews with detailed answers, curated for Databricks + GenAI + Agentic AI roles.

BONUS 03

WhatsApp Community

Network with 6,000+ engineers. Doubt resolution, code reviews and industry discussions — for life.

BONUS 04

Verified Certificate

Shareable on LinkedIn, signed by Sagar Prajapati. Showcase your Databricks + GenAI + Agentic AI mastery with one click.

Certificate of Completion

Zero to Databricks Expert — Complete Bundle

This certifies that
Your Name Here
has completed all 4 courses:
Foundation · Interview Ready · Agentic AI Bootcamp · 50 PySpark Qs
Sagar PrajapatiFounder, GeekCoders
2026Issue Year
// FAQ

Questions, answered

The complete bundle includes four separate courses combined at one price:
  • Course 1 — Azure Databricks Interview Ready Program: Foundation + 4 pipeline projects (Medallion, DLT+MLflow, GenAI Resume Screening, Production AI Agent)
  • Course 2 — Databricks Agentic AI Bootcamp: 4 production AI agent builds (Data Dictionary App, Resume & JD Matcher, Hospital Agent, Support Ticket Triage)
  • Course 3 — 50 PySpark Interview Questions: 50 questions across 10 categories, all solved end-to-end in notebooks
  • Lifetime access to all four, mentor guidance, WhatsApp community and verified certificate
All bundled at ₹9,999 — down from individual MRP of ₹25,000+.
Pipeline projects (Track 1) are about Databricks data engineering fundamentals — Medallion architecture, DLT, MLflow, and a first AI agent using Mosaic AI. They build the foundation.

AI agent builds (Track 2) go deeper into Agentic AI — you build four purpose-specific agents using LangGraph, Vector Search, multi-tool calling, and production deployment patterns. These are the rare skills that command 50 LPA+ in 2026.
The bundle gives you the technical depth and portfolio 30+ LPA roles demand — production Medallion architectures, DLT pipelines, MLflow workflows, LLM agents, and now full agentic AI systems on Databricks. Your jump still depends on your effort and how aggressively you interview, but the technical bar — the bottleneck for most engineers — gets solved here. 500+ alumni have already made this jump.
No. If you know basic Python and SQL, you can start from Course 1. Sagar walks through every Databricks concept before using it — from "I've heard of Delta Lake" to "I can design a Medallion pipeline and deploy a LangGraph agent."
100% pre-recorded with lifetime access — watch at your own pace, no missed classes, no timezone problems. Live mentor support happens through the WhatsApp community plus 1:1 DMs for blockers.
No catch. The individual courses total ₹25,000+ at MRP; the bundle exists to make the complete skill set accessible to genuinely motivated engineers. The real value is in the 8 production builds + mentor access — not arbitrary pricing tricks. You'll recover this in your first upgraded salary month.
WhatsApp directly at +91 91640 17543 — he replies personally. Or tap the floating WhatsApp button at the bottom-right. Full refund policy here.
// 4 courses · 8 builds · 50 questions

The complete toolkit.
The 30+ LPA journey.

Foundation. Pipeline projects. AI agents. Interview prep. Everything in one bundle.

₹25,000+ ₹9,999
Get the full bundle · ₹9,999
Get full bundle · ₹9,999