Datadives Academy

Two Residency Paths to Master

Choose your specialization: master production data pipelines or build autonomous AI agents. Both are 12 weeks of real projects with senior mentorship.

Data Infrastructure

Data Engineer Residency

Build production-grade data infrastructure. Master pipelines, orchestration, and real-time streaming.

  • Airflow, dbt, Spark, Kafka
  • AWS data lake architecture
  • Real client projects
  • 1:1 mentorship & code reviews

Rs. 49,999

12 weeks, remote

AI Agents

Agentic AI Residency

Build autonomous reasoning agents. Master LLM orchestration, tool-calling, and production guardrails.

  • LLM agents & multi-agent systems
  • Tool-calling & ReAct patterns
  • Memory systems & agentic RAG
  • Production deployment & monitoring

Rs. 49,999

12 weeks, remote

Supervised Project Residencies

Choose your path: Data engineering or agentic AI

Both programs provide real mentorship, portfolio-worthy projects, and verifiable completion certificates. Work on problems that matter.

Data Engineering

12-week supervised residency

Build production-grade data pipelines solving real infrastructure problems. You'll own end-to-end systems from source to analytics.

What you'll ship:

Apache Airflow DAG orchestration at scale
Real-time Kafka streaming pipelines
dbt transformation models with testing
AWS data lake architecture (Glue, S3, Redshift)
Performance-optimized SQL at 1B+ rows
Data quality frameworks and observability
Start your data journey

Agentic AI

8-week intensive residency

Build autonomous AI agents that think, plan, and act. From reasoning engines to multi-step workflows—you'll architect agents that actually work.

What you'll build:

LLM-powered agents with planning (ReAct, Tree of Thought)
Tool-calling frameworks and function composition
Multi-agent orchestration and communication
Memory systems (retrieval, context management, learning)
Agentic RAG with real-time feedback loops
Production guardrails (cost, latency, safety gates)
Start with AI agents

Why these residencies?

Data Engineering: The Foundation

Data engineering residency focuses on production systems—the infrastructure that every AI model, every ML pipeline, and every analytics dashboard depends on. You'll learn why 60% of AI projects fail: bad data. This program teaches you to prevent that.

Agentic AI: The Intelligence Layer

Agentic AI residency teaches you to build reasoning systems—agents that make decisions, delegate work, and adapt. This is cutting-edge: agents are where $50B+ of startup funding is flowing. Learn ReAct patterns, function calling, and multi-agent coordination before it becomes commodity.

Common to both residencies

Real projects

Not fake assignments. Real problems. Real impact.

Mentorship

Senior engineers. Code reviews. Architecture guidance.

Portfolio proof

GitHub contributions. Certificates. Verifiable completion.

Important: What this is (and isn't)

✓ Learning + real work: You'll contribute to actual projects, learn deeply, and build portfolio pieces.

✓ Honest credentials: Completion certificates, project proof, and verified contributions.

✗ Not employment: Residencies are learning programs, not jobs or fake experience schemes.

✗ No guarantees: We offer genuine mentorship and real work—but no promises of hiring or salary.

12-Week Program

From foundations to client delivery.

Residency Journey: Week 1-4 Foundations, Week 5-10 Real Project Build, Week 11-12 Senior Review leading to Client Delivery Team

Real projects from day one. Dedicated mentors. Trained on the same billable standards we deliver to clients. The residency is how we build—and scale—our delivery capacity.

Corporate AI Upskilling

Make your data team AI-native. 2–5 day intensive workshops for banks, fintechs, and enterprises — taught by engineers who ship this daily.

Custom On-Site

  • Tailored to your tech stack
  • Real data, real problems
  • Compliance-aware content

₹5–15L / $6K–18K per cohort

Public Cohorts

  • Mix of companies
  • Hands-on labs & capstone
  • 6–month community access

₹1L / $1.2K per person

Workshop Topics

→LLMs for data teams (RAG, fine-tuning, agents)
→AI evaluation & monitoring in production
→Building compliance-first AI systems
→Multi-modal data pipelines
→Prompt engineering for data ops
→Cost-effective scaling of AI

Our residents are trained on the same standards we bill clients for. Attend a workshop, see the work quality firsthand, and recruit directly. Or start a hiring conversation afterward.

Request a Corporate Workshop

We'll respond within 24 hours. No spam.

Standalone Online Courses

Learn at Your Own Pace

Self-paced online courses you can take independently. No prerequisites, no cohorts - start anytime and learn specific skills you need.

Separate from Residency Program

SQL Internals and Advanced SQL

Master joins, windows, CTEs, query plans, indexing basics, optimization, data modeling, slowly changing dimensions, and analytics-ready SQL.

Python for Data Engineering

Build production-style Python scripts, APIs, file processors, validators, logging, exception handling, packaging, and reusable utilities.

Apache Spark Internals

Understand Spark architecture, executors, partitions, shuffling, caching, joins, memory tuning, Spark SQL, performance debugging, and production Spark patterns.

AWS Data Engineering

Build cloud-native data workflows using S3, Glue, Lambda, Athena, DynamoDB, IAM, Step Functions, EventBridge, and monitoring patterns.

Apache Airflow

Learn DAG design, scheduling, sensors, operators, task dependencies, retries, backfills, SLAs, datasets, dynamic DAGs, and production orchestration practices.

dbt for Analytics Engineering

Learn dbt models, sources, seeds, snapshots, tests, macros, documentation, incremental models, and modern transformation workflows.

Data Quality and Observability

Build validation checks, anomaly detection rules, reconciliation logic, pipeline monitoring, alerts, audit tables, and data reliability dashboards.

Real-World Capstone Project

Build an end-to-end data engineering solution using batch ingestion, transformation, orchestration, quality checks, reporting, and documentation.

Select your course after clicking enroll

Who Should Apply

Is this program for you?

New Graduates

Who want real project confidence before their first job.

Interns

Who want genuine industry exposure beyond college projects.

Junior Data Engineers

Who want to level up with production-grade skills.

Software Engineers

Moving into data engineering and need structured learning.

Analysts

Transitioning to analytics or data engineering roles.

Working Professionals

Preparing for cloud data roles and certifications.