Data Engineering for Beginners with Python and SQL

Name: Data Engineering for Beginners with Python and SQL
Rating: 3.9 (1459 reviews)

From Novice to Data Engineer: Master Python and SQL for Data Processing

Created byKiril Spiridonov

Last updated 7/2026

English

BulgarianDanish

What you'll learn

Python Fundamentals
Variables, data types, and operators
Control flow (if statements, loops, etc...)
SQL Queries
Working with JSON and CSV data
Reading and writing files
Using libraries like requests to make HTTP requests
How to build functions and think like engineers
Data Cleaning and Transformation
Database Fundamentals (PostgreSQL)
Creating and managing databases and tables
Introduction to Postman
Testing RESTful APIs
Understanding what an API is
Retrieving data from an API

Coding Exercises

This course includes our updated coding exercises so you can practice your skills as you learn.

Course content

3 sections • 40 lectures • 3h 19m total length

Welcome!4:48
Course Structure2:33
Course Structure (Quick Reading)0:39
Getting Started17:10
This lecture will help you get started and understand programming as a concept.
Data Types11:04
Here you will learn about basic data types in Python
Strings (Quick Reading)2:03
Integers (Quick Reading)1:39
Conditional Statements15:54
Explore how conditional statements control program flow in Python, using if, elif, and else, with true/false checks and, or, and not logic, demonstrated through variable comparisons.
Lists11:10
Explore lists in Python, including creating, indexing, slicing, and reversing lists. Learn operations like append, insert, extend, pop, and sort with practical examples of length, sum, and clear.
Exploring Lists in Python (Quick Reading)4:40
Functions7:46
How to complete a coding exercise?5:22
Find the Maximum
Basic String Manipulation
Even or Odd
Calculate the Factorial
Loops8:05
Learn how to use lists with for and while loops, range for generating numbers, and indentation to print, square, and search list elements, including for-else and break logic.
Tuples2:37
Sets (Quick Reading)1:48
Find Unique Elements
Reverse a String
Calculate Sum of Digits
Check Palindrome
Fibonacci Series
Find the Nth Fibonacci Number
Check for Prime Numbers
Count Primes
Calculate Average
Count Occurrences in a List
Find the Missing Number
Find Common Elements in Two Lists
Remove Duplicates from a List
Count Occurrences of a Word
Check Balanced Parentheses
OOP Basics7:44
Explore object oriented programming in Python, covering encapsulation, abstraction, inheritance, and polymorphism through classes and objects, with constructors and method overriding demonstrated via car and electric car examples.
Introduction to Object-Oriented Programming (OOP)1:42
Find the Maximum Class Edition
Implement a Stack
Implement a Queue
Find The Closest Number
Find the Longest Consecutive Subsequence
Merge Sorted Lists
Jupyter Notebook7:23
Install and launch Jupyter Notebook using pip from the command line, then run Python notebooks in a browser. Explore notebooks, cells, memory management, and using pandas with API examples.
Pandas Introduction10:44
Explore pandas in a Jupyter notebook, import pandas as pd, and build a dataframe from a dictionary of names and ages; filter, group by name, and compute averages and oldest.
DataFrame and Series in Pandas1:46
Filtering in Pandas1:37
Pandas GroupBy and Aggregation1:57
Moving Averages in Pandas1:43
Data Manipulation
Interview Prep: Data Manipulation (Hard)
Article: Integrating Pandas with Matplotlib1:39

Install Postgres5:03
Relational Database Management Systems (RDBMS)5:57
SQL Fundamentals8:45
Discover Postgres and SQL basics with PgAdmin, creating a users table and performing queries using insert, select, where, group by, limit, and aggregates like avg.
SELECT and WHERE1:41
User Count Above 50
Order Analysis
Employee Database Query
Sales Analysis
WITH statement2:09
Employee Salary Analysis
UNION and UNION ALL1:53
Product Inventory Analysis
Customer Purchase Analysis
Order Analysis
Student Grades Analysis
Product Category Analysis
Order Date Analysis
Launch Date Analysis
PostgreSQL Quiz
NoSQL Databases2:42
Streaming Data Introduction4:13
Article: Vector Databases1:49
What is DataOps2:58

What is an API (Quick Reading)2:33
Understanding APIs (Extensive Reading)4:44
GET Request1:26
POST Request1:31
Postman4:27
Use Postman to test API requests, generate Python requests code, and extract JSON data for loading into a database or files.
Extract Data13:57
Extract data from a public API and test with Postman before saving it locally via an ETL workflow. Convert JSON to a Pandas DataFrame, transform fields, and export to Excel.
Interview Prep: ETL

Requirements

No prerequisites except high motivation!

Description

Are you ready to embark on a journey into the world of data engineering? Welcome to "Data Engineering for Beginners with Python and SQL" – the course that will empower you to build a strong foundation in data engineering, regardless of your prior experience.

In today's data-driven world, the demand for skilled data engineers is soaring, and this course is designed to help you seize the opportunities this field has to offer. Whether you're an aspiring data professional, a business analyst, or simply curious about the intricacies of data processing, this course is your gateway to acquiring the essential skills.

What You'll Learn:

SQL Mastery: Dive headfirst into SQL (Structured Query Language), the cornerstone of data management. You'll learn how to manipulate and query data effectively, ensuring you have a solid grasp of this fundamental skill.
Python: Explore the power of Python for data engineering and not only. We'll cover the basics and take you on a journey through Python possibilities.
ETL (Extract, Transform, Load) Processes: Gain insights into ETL processes, a critical component of data engineering. Discover how to efficiently extract data from various sources, transform it to meet your needs, and load it into target systems.

Course Highlights:

Materials and Exercises: This course focuses on practical learning. We believe in the "learn by doing" philosophy, so you'll find a wealth of materials and hands-on exercises to reinforce your knowledge.
Comprehensive Resources: Access a comprehensive collection of resources, including coding examples and reference materials to aid your learning journey.
Minimal Video, Maximum Learning: We understand the value of your time. While there will be instructional videos, engaging exercises and resources will be emphasized, allowing you to learn at your own pace.

Important: In this engineering course, it's all about how you think and problem-solve. Instead of just watching videos and copying them, the focus is on finding the right information and using it to tackle tasks. Learning how to think is a crucial part of the process. Feel free to ask questions under each exercise or message the instructor directly. Expect a response within 24 hours.

Who this course is for:

Aspiring Data Engineers
Data Enthusiasts
Programming Novices
SQL Beginners
Career Switchers
Students and Recent Graduates
Business Analysts
Entrepreneurs and Start-up Founders
Self-Learners
Professionals Seeking Data Skills

Data Engineering for Beginners with Python and SQL

What you'll learn

Explore related topics

Coding Exercises

Course content

Python Basics For Data Engineers24 lectures • 2hr 14min

SQL and Databases10 lectures • 37min

API Usage6 lectures • 29min

Requirements

Description

Who this course is for: