Data Engineering with Python, SQL & Spark Full Stack Course

Name: Data Engineering with Python, SQL & Spark Full Stack Course
Rating: 4.9 (28 reviews)

Master Data Engineering from scratch to advanced and Learn Python, SQL, GIT, DSA and Docker and many more with Projects

Created byKasi Gopi

Last updated 7/2026

English

What you'll learn

Learn the fundamentals of data engineering, including databases, data warehousing, ETL pipelines, and big data concepts from beginner to advanced level.
Build scalable data pipelines using modern tools and technologies such as SQL, Python, Apache Spark, Hadoop, Kafka, and cloud platforms.
Master data processing, transformation, storage, and analytics techniques for handling real-world structured and unstructured data.
Develop hands-on experience through practical projects, cloud integration, and industry-standard workflows to become a job-ready data engineer.

Course content

6 sections • 69 lectures • 47h 2m total length

Introduction6:13

Getting Started with Python30:58
Primitive Types32:17
Control Flow37:38
Functions38:10
Data Structures1:17:31
Exceptions22:12
Python Classes Part 136:55
Explore Python classes as the first part of the data engineering full stack course, building foundational skills for data-driven programming with Python.
Python Classes Part 246:02
Modules17:21
Python Standard Library59:42
Python Package Index45:42
Popular Python Packages54:08
Building Web Applications with Django Part - 11:01:06
Building Web Applications with Django Part - 257:32
Machine Learning with Python46:48
Dice Rolling Game Project in Python7:24
Number Guessing Game and Rock Paper Scissor Projects in Python33:53
Currency Converter and Quiz Game Projects in Python39:57
Tic Tac Toe Game Project in Python29:20
Todo List and Simple Text Editor Projects in Python35:03
Pig Dice Game and Cows and Bulls Game Projects in Python32:29
Password Strength Checker and Password Generator projects in Python19:21
Word Guessing Game and Slot Machine Game Projects in Python40:10
ATM Simulation Project in Python Programming36:24
Importance of Python Programming6:47

Getting Started with SQL24:26
Retrieving Data From a Single Table57:12
Learn how to retrieve data from a single table using Python, SQL, and Spark, enabling efficient data querying in data engineering workflows.
Retrieving Data From Multiple Tables48:01
Inserting, Updating, and Deleting Data41:50
Summarizing Data in SQL30:22
Writing Complex Query38:21
Essential MySQL Functions31:19
Views in SQL18:17
Stored Procedures47:59
Learn how stored procedures streamline data workflows by creating and using them with Python, SQL, and Spark, empowering efficient data engineering practices.
Triggers and Events20:51
Transactions and Concurrency42:35
Data Types24:02
Designing Databases Part 159:38
Designing Databases Part 259:58
Indexing for High Performance52:26
Securing Databases in SQL14:13
Learn to secure MySQL databases by creating restricted user accounts, assigning precise privileges for applications and admins, and using grants, revokes, and password practices.

Getting Started with DSA17:33
Explore core data structures: arrays, linked lists, stacks, queues, hash tables, trees, and graphs, while mastering big O notation, algorithm analysis, and interview-focused problem solving for scalable coding.
Arrays29:18
Linked Lists44:44
Master linked lists within the data engineering context, leveraging Python, SQL, and Spark to model and traverse data structures.
Stacks41:58
Queues51:48
Learn how queues streamline data engineering tasks using Python, SQL, and Spark, enabling efficient data processing and workflow management.
Hash Tables1:06:06
Explore hash tables and their use in data engineering workflows. Apply concepts with Python, SQL, and Spark to optimize lookups and data management.
Binary Trees1:14:20
AVL Trees48:46
Heaps54:04
Trees46:32
Graphs1:06:45
Undirected Graphs58:11
Sorting Algorithms1:12:25
Explore sorting algorithms within data engineering, applying Python, SQL, and Spark to organize data efficiently.
Searching Algorithms34:09
String Manipulation Algorithms56:21

Getting Started with Git13:58
Creating Snapshots57:53
Create snapshots to capture data states within data engineering workflows. Master the use of Python, SQL, and Spark in this full stack course.
Browsing History42:53
Explore how to manage and analyze user browsing history data using Python, SQL, and Spark techniques within a data engineering workflow.
Branching1:11:35
Collaboration16:40
Rewriting History44:31
Delve into rewriting history using data engineering techniques with Python, SQL, and Spark to transform data into scalable, actionable insights.

Requirements

You will learn from scratch and You do not need to have any experience in this course

Description

The Complete Data Engineering Bootcamp from Beginner to Advanced is a comprehensive and industry-focused program designed to transform beginners into confident and skilled data engineering professionals. Whether you are a student, software developer, database administrator, analyst, or someone curious about big data technologies, this course provides a step-by-step roadmap to mastering modern data engineering concepts and tools used by top technology companies worldwide.

In this bootcamp, you will begin with the fundamentals of data engineering, understanding how data flows through modern systems and how organizations collect, process, store, and analyze massive amounts of information. You will learn essential database concepts, SQL programming, data modeling, and data warehousing techniques that form the foundation of every successful data engineering pipeline.

This bootcamp emphasizes practical learning through projects, exercises, and real-world scenarios. You will build data pipelines, automate workflows, manage streaming data, optimize databases, and work with structured as well as unstructured data. By the end of the course, you will understand how enterprise-level data systems are designed and maintained efficiently.

By completing this bootcamp, you will gain the confidence and practical skills required to pursue careers such as Data Engineer, Big Data Engineer, ETL Developer, Cloud Data Engineer, Analytics Engineer, or Data Platform Developer. You will also develop a strong portfolio of projects that demonstrate your expertise to employers and clients.

Who this course is for:

It is for anyone who wants to master Data Engineering from beginner to Advanced

Data Engineering with Python, SQL & Spark Full Stack Course

What you'll learn

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Course content

Introduction1 lecture • 6min

Python Programming with Projects for Data Engineering25 lectures • 15hr 45min

SQL for Data Engineering16 lectures • 10hr 12min

DSA for Data Engineering15 lectures • 12hr 43min

GIT for Data Engineering6 lectures • 4hr 8min

Docker for Data Engineering6 lectures • 4hr 10min

Requirements

Description

Who this course is for: