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Bestseller Recently updated Programming · Data

Data Engineering Bootcamp

Go from zero to a job-ready data engineer — SQL, data modeling, ETL pipelines, and warehouses, all built on one real ShopStream dataset.

4.2 (41 ratings) Created by Ananya Iyer
Beginner 105 lessons 27h 34m Updated Jun 2026 English
Preview this course
₹129 ₹349 63% off
incl. GST
left at this price!
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7-day money-back guarantee

What you'll learn

Write SQL fluently — from SELECT and JOINs to aggregation, CTEs, and window functions
Model data for analytics with fact and dimension tables, star and snowflake schemas
Build reliable ETL/ELT pipelines with extraction, transformation, loading, and quality checks
Design and load a layered data warehouse, including slowly changing dimensions
Turn raw tables into trusted, documented business metrics as an analytics engineer
Ship an end-to-end ShopStream project you can put on your portfolio

This course includes

27h 34m of on-demand content
105 lessons across 16 sections
Access on mobile and desktop
Certificate of completion
Lifetime access
Curriculum

Course content

16 sections · 105 lessons · 27h 34m

What is Data Engineering? Preview 12 min
The Modern Data Stack Preview 12 min
Data Engineering Career Roadmap Preview 10 min
Setting Up Your Learning Environment 25 min
Python & Git Quick Setup 20 min
Section Quiz · Introduction to Data Engineering 10 min

Understanding Data 10 min
Data Formats (CSV, JSON, Parquet, Avro) 14 min
The Data Lifecycle 10 min
Batch vs Real-Time Data 12 min
Section Quiz · Data Fundamentals 8 min

Introduction to Databases 10 min
Tables, Rows, and Columns 10 min
Primary Keys and Foreign Keys 12 min
Database Relationships 12 min
Database Normalization (1NF→3NF) 16 min
Section Quiz · Relational Databases Fundamentals 10 min

Your First SQL Query (SELECT / FROM) 12 min
Filtering Data (WHERE) 14 min
Sorting and Limiting Results (ORDER BY / LIMIT) 12 min
Working with NULL Values 12 min
Calculated Columns & Aliases 12 min
SQL Practice Session 30 min
Section Quiz · SQL Fundamentals 12 min

Aggregate Functions 12 min
Grouping Data (GROUP BY) 14 min
Filtering Aggregated Results (HAVING) 12 min
SQL Joins Part 1 (INNER JOIN) 16 min
SQL Joins Part 2 (LEFT / RIGHT / FULL) 16 min
SQL Joins Part 3 (Self & Cross Joins) 14 min
SQL Practice Project (Multi-table Analysis) 35 min
Section Quiz · SQL Intermediate 14 min

Subqueries 16 min
Common Table Expressions (CTEs) 14 min
Window Functions Part 1 (Ranking) 18 min
Window Functions Part 2 (Running totals, moving averages) 18 min
CASE Statements 14 min
Query Optimization Basics 18 min
SQL Data Engineering Project 40 min
Section Quiz · Advanced SQL for Data Engineers 15 min

Why Data Modeling Matters 10 min
OLTP vs OLAP 12 min
Fact Tables 14 min
Dimension Tables 14 min
Star Schema 16 min
Snowflake Schema 14 min
Designing Your First Analytics Model 35 min
Section Quiz · Data Modeling 15 min

Python for Data Engineers in 30 Minutes 30 min
What is ETL? 10 min
ETL vs ELT 12 min
Data Extraction 16 min
Data Transformation 18 min
Data Loading 16 min
Common ETL Challenges 16 min
Section Quiz · ETL Fundamentals 15 min

ETL Pipeline Architecture 14 min
Incremental Processing (watermarks, CDC basics) 18 min
Data Quality Checks 16 min
Logging and Monitoring 14 min
Scheduling Workflows 14 min
Building a Complete ETL Pipeline 50 min
Section Quiz · Building ETL Pipelines 12 min

What is a Data Warehouse? 12 min
Warehouse vs Database 12 min
Warehouse Layers (raw / staging / analytics) 14 min
Partitioning and Clustering 14 min
Slowly Changing Dimensions (Type 1 & Type 2) 18 min
Building a Warehouse Model 50 min
Section Quiz · Data Warehouses 12 min

What is Analytics Engineering? 10 min
Transforming Raw Data into Models 16 min
Business Metrics 18 min
Building Analytical Models 20 min
Data Documentation 14 min
Section Quiz · Analytics Engineering 10 min

Anatomy of a Modern Analytics Platform 12 min
E-Commerce Analytics System 16 min
Product Analytics System 18 min
Marketing Analytics System 16 min
Executive Reporting Systems 14 min
Section Quiz · Real-World Analytics Systems 10 min

Data Quality 14 min
Data Governance Basics 12 min
Data Lineage 12 min
Data Security 16 min
Reliable Data Pipelines 16 min
Section Quiz · Data Governance & Reliability 10 min

Project Overview 20 min
Source System Design 30 min
ETL Development 60 min
Data Warehouse Design 45 min
Analytics Layer 45 min
Final Business Reporting 45 min
Section Quiz · Capstone Project: ShopStream End-to-End 12 min

Common Data Engineering Interview Questions 40 min
Data Engineering Case Studies 25 min
Portfolio Building 30 min
Next Learning Paths 20 min
Section Quiz · Industry Readiness 8 min

Glossary 15 min
Cheat Sheets 10 min
ShopStream Dataset Dictionary 14 min
Suggested Pacing 8 min
Where to Go Next 10 min

Requirements

  • No prior data engineering experience required
  • Basic comfort using a computer and installing software
  • A willingness to write SQL and a little Python (both taught from scratch)

Description

What you'll learn

A complete, beginner-friendly path into data engineering — the craft of moving, shaping, and serving data so a business can trust it. Every section builds on the last, and a single realistic e-commerce dataset (ShopStream) runs through the whole course so the skills connect into one coherent system.

The journey

You start by building the mental map of where data engineering sits, then learn relational databases and SQL from the very first SELECT all the way to window functions and query optimization. From there you design data models, build ETL/ELT pipelines, and load a layered data warehouse — before stepping up into analytics engineering, real-world analytics systems, governance, and reliability.

Capstone & readiness

The course finishes with an end-to-end ShopStream capstone — source design, ETL, warehouse, analytics, and reporting — plus an industry-readiness section covering interview questions, case studies, and portfolio building. A reference appendix (glossary, cheat sheets, dataset dictionary, pacing, and next steps) backs the whole course.

Who this is for

Beginners and career-switchers who want a clear, complete route into data engineering. No prior experience is required — SQL and the small amount of Python you need are taught from scratch.

Topics covered

data-engineering sql etl data-warehouse analytics
Your instructor
A

Ananya Iyer

Python & Big Data Engineer · 10 yrs · Data Engineering Lead, Tessellate

4.2 course rating 1 courses

Ananya has built data platforms in Python for a decade, wrangling everything from gnarly ETL jobs to petabyte-scale Spark pipelines. She loves the craft of clean, testable Python and teaching the data-engineering fundamentals that survive whichever framework is trendy this year.

4.2 course rating · 41 ratings

Z
Zora Hintz Sr.
1 year ago

Average. The instructor is clear, but a few more concrete examples would have helped a lot.

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K
Katlyn Stracke
4 months ago

A complete, well-thought-out course. I came in a beginner and finished feeling genuinely confident.

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P
Prof. Idell O'Keefe
11 months ago

This exceeded my expectations. Clear delivery, great examples, and just the right amount of depth.

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A
Angelo Daugherty
1 year ago

Brilliant. I finally understand topics that always confused me. The hands-on bits made all the difference.

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  • Report this review

Frequently asked questions

Yes — once you enroll, the course is yours to revisit forever. New revisions and bonus lessons are added at no extra cost.

Finish every lesson and you'll unlock a shareable certificate you can post on LinkedIn or include with job applications.

If the course isn't a fit, request a refund within 7 days of purchase — no questions asked.

Code, slides, and worksheets are downloadable on each lesson page. Videos stream from our CDN so you can watch on any device.

Each course states its level in the hero. If you're comfortable with the prerequisites listed, you're ready to start.

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