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Learn MoreData Engineering: From Zero to Hero
Rating: 4.1 out of 54.1(6 ratings)
26 students
Data Engineering: From Zero to Hero
Master the Fundamentals of Modern Data Engineering — No Experience Needed
Created byRicardo Gonçalves
Last updated 4/2026
English
English [Auto],
What you'll learn
- What is Data Engineering?
- Identify Data Sources and Data Destinations
- Define what a Data Pipeline is
- Interact with an API using Python
- Cleaning a Dataset using SQL and Python
- Identify Transformations that can be applied to Data with Python and SQL
- Orchestrate Data Pipelines with Airflow
Explore related topics
Course content
8 sections • 123 lectures • 7h 4m total length
- Welcome to the Course0:59
In this lecture, I will welcome you into this course and tell you what you can expect from it.
- About Me, You and this Course2:19
In this lecture, I will introduce myself, I will talk about who I think you are (and I hope I'm right) and I will detail the course design.
- Course Outline1:38
In this lecture, I will walk you through the course outline, introducing you to what will be covered in each section.
- Things you will need0:44
In this lecture, I will present you the things you will need to install or register to in order to follow along with this course practical side.
- [OPTIONAL] Installing Python on MacOS1:45
In this lecture, let's go on through the process of installing Python on your Mac.
- [OPTIONAL] Installing VSCode on MacOS6:22
In this lecture, let's see how you can install VSCode on MacOS
- [OPTIONAL] Creating a Virtual Environment on MacOS2:26
In this lecture, I'll show you how you can create a Python Virtual Environment on MacOS
- [OPTIONAL] Installing Relevant Python Libraries on Virtual Environment on MacOS2:00
In this lecture, I'll go through the installation of some useful Python libraries on the virtual environment you just created, on a MacOS.
- [OPTIONAL] Testing Setup on MacOS4:14
In this lecture, we'll go through testing the setup we have created for developing data solutions with Python.
- [OPTIONAL] Jupyter Notebooks4:14
In this lecture, I go through Jupyter Notebooks, a useful tool for a Data Engineer
- Section Outline0:54
In this lecture, I will guide you through the Section 2 Outline
- What is Data Engineering?3:25
In this lecture, I will present you one definition of Data Engineering and will tell you why this is a very high demand area.
- What is a Data Engineer?5:30
In this lecture, I will present you the definition of Data Engineer, I'll show you what a Data Engineer should do and present you some common examples of tasks a Data Engineer does.
- Data Engineering Skills & Tools3:35
In this lecture, I will present you a list of skills and tools that a good Data Engineer should be acquainted to.
- Section 2 Sum Up2:18
In this lecture, I will present you with a sum up of what we've covered on Section 2.
- Data Engineering Quiz
- Section Intro0:42
In this lecture, I'll welcome you to the third section of this course and present you the learning objectives.
- Section Outline1:10
In this lecture, I'll guide you through the outline for this section.
- The Basics of Computers4:56
In this lecture, I will walk you through the basics of computers so that you can have a solid base (or review) of these important concepts. We will talk about CPU, RAM and computer networks.
- The Basics of Computers
- On-Prem vs. The Cloud2:44
In this lecture, I'll explore two environments for Software and Data Operations: on-premises and the cloud.
- Cloud Services3:32
In this lecture, I will talk about the different Cloud Services and give some examples on how they might help you with your data operations.
- Quiz
- All Things Data: What is Data1:38
In this lecture, I'll show you one possible definition of data and relate that to both Information and Knowledge.
- All Things Data: Structure3:00
In this lecture, I'll address the different types of Data Structure: Structured, Semi-Structured and Unstructured data.
- All Things Data: Data Types1:29
In this lecture, I'll introduce you to the main data types.
- All Things Data: Data Formats5:38
In this lecture, I'll guide you through the most common data file formats.
- All Things Data: Properties of Big Data1:52
In this lecture, I'll talk about what makes the data Big.
- The Analytical World vs. the Operational World4:07
In this lecture, I introduce you to the Analytical world and I present you with what differentiates it from the operational world of a company.
- Section 3 Sum Up0:54
In this lecture, I present you with a sum up of what we've covered on Section 3.
- Quiz
- Section Intro0:48
In this lecture, I'll welcome you to the fourth section of this course and present you the learning objectives.
- Section Outline0:45
In this lecture, I'll guide you through the outline for this section.
- Data Sources Intro1:36
In this lecture, I will present you the typical data sources from where Data Engineers can get data from.
- Data Sources: Operational Databases0:59
In this lecture, I will present you details about Operational Data Bases.
- Data Sources: API7:18
In this lecture, I will give you more depth on the way you can retrieve data from an API.
- Data Sources: More1:20
In this lecture, I will talk about other data sources that you can be exposed to as a Data Engineer.
- Quizz
- Getting List of Earthquakes from API
- Getting List of Earthquakes from API - Solution21:59
In this lecture, I will present you one solution for the assignment by calling an API and getting a list of specific traits of earthquakes
- Data Repositories: Intro1:24
In this lecture, I will introduce you to the most common data repositories.
- Data Repositories: DW, DL and LH2:23
In this lecture, I will distinguish Data Warehouses, Data Lakes and Lakehouses and enumerate the advantages and use cases of each one over the others.
- Data Repositories: Data Marts0:45
In this lecture, I will talk a little about data marts as data repositories.
- Data Repositories: NoSQL2:52
In this lecture, I will present you alternative data bases which don't rely on structured data or structure querying language.
- Data Repositories: API0:42
In this lecture, I will talk again about API, however this time as possible data repositories.
- Data Repositories
- Data Pipelines3:22
In this lecture, I will talk about the essential concept of a Data Pipeline.
- Data Pipelines: Batch vs. Real Time5:32
In this lecture, I will give you the differences between batch and real time data processing.
- Data Pipelines
- Section 4 Sum Up1:44
Connect data sources to repositories through pipelines, applying ETL or ELT transformations. Compare batch and real-time pipelines to match latency needs and use cases.
- Section Intro1:15
In this lecture, I will introduce you to Section 5.
- Section Outline1:16
In this lecture, I will guide you through the outline for this Section 5.
- What is Data Modeling?1:36
In this lecture, I will present you a definition of Data Modeling and its importance in Data Engineering operations.
- The Star Schema2:40
In this lecture, I will present you the concept of a Star Schema, one of the most common Data Modeling techniques.
- The Star Schema: Fact Tables4:48
In this lecture, I will detail Fact Tables, a central piece in the Star Schema Model.
- The Star Schema: Dimension Tables8:42
In this lecture, I will detail Dimension Tables, a key concept to provide context to your analysis using a Star Schema.
- Practical Example: The Star Schema7:27
In this lecture, I will guide through a practical example of a Star Schema.
- The Star Schema
- The Snowflake Schema2:38
In this lecture, I will present you a Data Modeling alternative: the Snowflake Schema.
- Practical Example: The Snowflake Schema4:29
In this lecture, I will guide through an example of a Snowflake Schema.
- The Snowflake Schema
- Data Vault2:14
In this lecture, I will present you yet another Data Modeling approach: the Data Vault.
- Medallion Model1:59
In this lecture, I will talk about the Medallion Model and how this can be useful for your Data Pipelines.
- Practical Example: Medallion Model5:53
In this lecture, I will present you an example of a Medallion Model implementation.
- Medallion Model
- Building a Data Model3:23
In this lecture, I will introduce you to the BEAM Methodology that will help you model data.
- Practical Example: Building a Data Model4:20
In this lecture, I will guide you through an example of applying the BEAM Methodology for Data Modeling.
- Optimizing Your BI Solution4:00
In this lecture, I will present you some solutions to optimize your BI approach.
- Section 5 Sum Up1:18
In this lecture, I will present you a summary of the topics of this section.
- Section Intro0:19
In this lecture, I will introduce you to Section 6 which will teach you about this essential tool for Data Engineering: SQL.
- Section Outline1:22
In this lecture, I will guide you through the outline for this Section 6.
- Introduction to SQL3:04
In this lecture, I'll walk you through a first introduction to SQL Programming Language.
- Important SQL Concepts6:39
In this lecture, I'll introduce you to the most important SQL concepts.
- Introduction to Snowflake3:30
In this lecture, I'll give a brief, but deep introduction to this very modern and important Data tool which is Snowflake.
- Register on Snowflake2:31
In this lesson, let's setup a Snowflake account for you to use to learn SQL
- Snowflake: A Walkthrough5:19
In this lesson, we'll take a walkthrough Snowflake UI: Snowsight.
- Preparing Snowflake for this SQL Crash Course8:50
In this video, I'll guide you through the project setup for Snowflake which is going to be very useful for our practical examples and assignments.
- Basic Data Retrieval5:22
In this lecture, let's see how we can use SQL to retrieve data from database tables.
- Practical Example: Basic Data Retrieval6:56
In this video, I'll walk you through a few examples of basic data retrieval using SQL on Snowflake.
- Assignment Intro: Basic Data Retrieval0:45
In this video, let me introduce you to this first assignment.
- Basic Data Retrieval
- Assignment Solution: Basic Data Retrieval4:02
In this video, let's go over a possible solution of Assignment #1.
- Aggregations and Grouping with SQL5:08
In this lecture, I'll walk you through aggregations and groupings with SQL, which are the cornerstone of doing data analysis with SQL.
- Practical Example: Aggregations and Groupings with SQL7:06
In this Practical Example, let's see Aggregations and Groupings in practice on Snowflake.
- Assignment Intro: Aggregations and Groupings with SQL0:25
In this video, I'll introduce you to the second assignment.
- Aggregations and Groupings with SQL
- Assignment Solution: Aggregations and Groupings with SQL5:05
In this video, let's go over a possible solution of Assignment #2.
- SQL: the Basics
- Joining Tables5:12
In this lecture, we'll talk about joining tables, the different types of joins and the strategy thinking behind them.
- Practical Example: Joining Tables13:53
In this video, let's see an example of joins.
- Assignment Intro: Joining Tables0:30
In this video, let's introduce assignment number 3.
- Joining Tables
- Assignment Solution: Joining Tables5:12
In this video, let's go over a possible solution of Assignment #3.
- Joining Tables
- SQL Subqueries3:11
In this lecture, we'll focus on SQL Subqueries, which can help you tackle query complexity.
- Practical Example: SQL Subqueries2:19
In this video, let's see an example of SQL Subqueries.
- SQL CTE1:51
In this lecture, we'll explore SQL CTE (Common Table Expressions).
- Assignment Intro: SQL CTE0:20
In this video, let's introduce assignment number 4.
- SQL CTE
- Assignment Solution: SQL CTE4:50
In this video, let's go over a possible solution of Assignment #4.
- SQL Window Functions6:27
In this lecture, I'll walk you through a power full tool for Data Engineers: SQL Window Functions.
- SQL Window Functions: Common Examples2:16
In this lecture, let's see some common use cases for SQL Window Functions.
- Practical Example: SQL Window Functions4:12
In this video, let's see an example of SQL Window Functions.
- Assignment Intro: SQL Window Functions0:31
- SQL Window Functions
- Assignment Solution: SQL Window Functions4:54
- Advanced SQL Features
- SQL Computing Order1:02
In this lecture, I'll walk you through the typical SQL Execution order.
- Data Cleaning with SQL1:33
In this lecture, let's briefly discuss data cleaning with SQL (which we'll deepen later on the course).
- Data Transformations with SQL0:47
In this lecture, let's briefly discuss data transformations with SQL (which we'll deepen later on the course).
- Building Data Marts with SQL6:00
In this lecture, let's go through an example of how SQL can help you build a Data Mart to solve a given business need in terms of analytics requests.
- Section Sum Up1:05
In this lecture, I will present you a summary of the topics of this section.
- Section Intro0:53
In this lecture, I will introduce you to this sixth section of this course.
- Section Outline0:45
In this lecture, I will guide through the outline of Section 6.
- What is Data Wrangling?1:24
In this lecture, I will present you the definition of Data Wrangling.
- Data Cleaning Intro0:58
In this lecture, I will talk about Data Cleaning and describe the most common cleaning operations.
- Data Cleaning: Data Deduplication4:23
In this lecture, I will present you ways to remove duplicates from your data.
- Data Cleaning: Missing Data3:19
In this lecture, I will present you ways to handle missing data.
- Data Cleaning: Standardization1:57
In this lecture, I will present you ways to standardize data.
- Practical Example: Data Cleaning with SQL15:35
In this lecture, I will present you a data cleaning example using SQL.
- Assignment Intro: Data Cleaning with Python1:10
- Data Cleaning with Python
- Assignment Solution: Data Cleaning with Python14:37
In this lecture, I'll go through the solution of the Assignment "Data Cleaning with Python" step by step.
- Data Cleaning
- Data Transformation Intro0:53
In this lecture, I will introduce you to Data Transformation processes.
- Data Transformation: Sorting1:02
In this lecture, I will talk about the Sorting operation.
- Data Transformation: Aggregation1:53
In this lecture, I will talk about Data Aggregations.
- Data Transformation: Filters1:26
In this lecture, I will talk about Filtering operations.
- Data Transformation: Window Functions2:10
In this lecture, I will introduce you to useful window functions that can help you with calculations.
- Assignment Intro: Data Transformation with Python0:58
In this lecture, I'll present you your next Data Transformation assignment in which you'll use Python and apply the techniques you learnt on this section!
- Data Transformation with Python
- Assignment Solution: Data Transformation with Python5:32
In this lecture, I'll walk you step by step through the solution to the Data Transformation with Python Assignment.
- Data Transformations
- Data Validation3:23
In this lecture, I will discuss Data Validation.
- Data Validation
- Section Sum Up1:30
In this lecture, I will present you a summary of the topics discussed on Section 6.
- Section Intro0:55
In this lecture, I will welcome you to Section 7.
- Section Outline1:14
In this lecture, I will guide you through Section 7 outline.
- What is Data Pipelines Orchestration?3:17
In this lecture, I will discuss the need for Data Pipeline Orchestration.
- Data Pipelines Orchestration
- Airflow: An Introduction4:21
In this lecture, I will introduce you to Apache Airflow.
- Airflow: Quick Tour3:42
In this lecture, I will give you a quick, practical tour to Apache Airflow.
- Airflow DAGs6:34
In this lecture, I will present you the definition of a Directed Cyclical Graph and its relationship with Airflow pipelines.
- Airflow Tasks & Dependencies6:05
In this lecture, I will present you Airflow tasks.
- Airflow Operators & Sensors5:12
In this lecture, I will explore Airflow Operators with you.
- Practical Example: Airflow DAGs4:14
In this lecture, I will guide you through an example of an Airflow DAG.
- Airflow UI2:36
In this lecture, I will present you more details about Airflow UI.
- Airflow UI: A Tour4:26
In this lecture, I will walk you through Airflow UI.
- Airflow
Requirements
- Basic programming knowledge with Python is highly recommended, but not mandatory
- Basic knowledge of SQL
- Familiarity with Computer Science
Description
Step into the world of Data Engineering with confidence and curiosity — no prior experience is required!
"Data Engineering: From Zero to Hero" is the perfect starting point for anyone eager to understand how data is collected, transformed, stored, and used in today’s tech-driven world.
Whether you're an aspiring data professional, a curious developer, or someone trying to switch careers, this course will walk you through the core concepts, tools, and architectures that power data pipelines in modern organizations.
In this course, you’ll learn:
What Data Engineering really is — and why it's crucial today
What a Data Engineer does on a daily basis and what kind of skills one needs to have
How data flows through an organization using ETL/ELT pipelines
Key components of a modern data stack: databases, data lakes, data warehouses, orchestration tools, and more
The essentials of data modeling, including star schema, normalization, and denormalization
Why Data Pipelines orchestration is important and the basics of implementing it
This course combines clear explanations with practical examples to help you build a solid foundation in data engineering — the backbone of every data-driven company.
By the end of the course, you’ll have the confidence and clarity to dive deeper into specialized tools and start exploring hands-on projects.
Who this course is for:
- Data Professionals who want to become Data Engineers
- Beginner Data Engineers
- Software Engineers curious about Data Engineering
- Data Analysis Professionals curious about Data Engineering