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Advanced SQL for Data Engineering

Master advanced SQL for data engineering skills by taking a masterclass from an industry expert

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  • Institute of Analytics
  • The Association of Data Scientists
  • E-Learning Quality Network
  • European Agency for Higher Education and Accreditation
  • Global Association of Online Trainers and Examiners

Skill level:

Advanced

Duration:

2 hours
  • Lessons (2 hours)

CPE credits:

3
CPE stands for Continuing Professional Education and represents the mandatory credits a wide range of professionals must earn to maintain their licenses and stay current with regulations and best practices. One CPE credit typically equals 50 minutes of learning. For more details, visit NASBA's official website: www.nasbaregistry.org

Accredited:

certificate

What You Learn

  • Learn data engineering fundamentals for career growth.
  • Gain expertise in advanced SQL for data storage, manipulation, and retrieval.
  • Work with data types like Array and JSON for complex data.
  • Understand database schemas and structures to optimize performance.
  • Acquire technical skills for data engineering interviews.

Topics & tools

SQLdata engineeringprogrammingdata preprocessing

Your instructor

Course OVERVIEW

Description

CPE Credits: 3 Field of Study: Information Technology
Delivery Method: QAS Self Study
In this increasingly data-driven world, proficient SQL skills are highly valuable in numerous roles and industries. This Advanced SQL for Data Engineering course offers a unique blend of theory and practice to deepen your understanding of complex SQL concepts and database design topics. Master essential SQL skills for data engineering through hands-on exercises. Improve your database management, maintenance, modeling, and querying capabilities, and learn about timestamps, functions, advanced data types, etc.

Prerequisites

  • Any SQL environment (such as PostgreSQL, MySQL Workbench, SQLite, or an online SQL editor)
  • Strong understanding of SQL fundamentals, including joins, subqueries, and aggregations.
  • Familiarity with data engineering concepts (ETL, data pipelines) is helpful but not mandatory.

Curriculum

46 lessons 1 exam
  • 1. Setting up the environment and overview of relational databases
    14 Min
    This section serves as both an introduction and foundation for the advanced SQL concepts you will encounter later in the course. It kicks off with a practical guide on setting up your SQL environment, providing you with step-by-step installation instructions to ensure you are well-prepared to start your SQL journey. The following lesson takes a step back to understand the fundamental framework of data storage and management: Relational Databases. We'll delve into how data is structured, related, and accessed within these systems, providing you with the context needed to understand more advanced topics. Next, we dive into the various subsets of SQL - Data Definition Language (DDL), Data Manipulation Language (DML), Data Query Language (DQL), and Data Control Language (DCL). Each of these categories plays a different but vital role in the management and manipulation of data, and understanding their roles and usage will be critical for your progression. Lastly, the section concludes with an in-depth look at SQL syntax. Good command of SQL syntax is crucial to write efficient and error-free SQL queries. This lesson will ensure you're well-versed in the language of SQL, providing a solid foundation upon which to build as the course progresses.
  • 2. Manipulating databases: Mastering essential SQL statements
    18 Min
    This part of the course equips you with the tools to manipulate databases using key SQL statements. Beginning with the creation of databases, we explore how to modify, add to, update, and delete data using various SQL commands. You'll learn how to combine operations using the MERGE statement and wrap up the section by learning how to safely remove data and tables with the DROP statement. This section will empower you to control your databases effectively.
  • 3. Timing is everything: managing and manipulating DateTime in SQL
    14 Min
    It is time to delve into the world of DateTime in SQL. You'll understand the importance and varied types of DateTime data in SQL, how timezones affect data, and the use of intervals for calculations. By the end of this section, you'll be proficient in handling date and time-based data, a crucial aspect of any database management system.
  • 4. Complex data types: ENUMs, ARRAYs, Ranges, and Nested data in SQL
    18 Min
    We venture into the realm of complex data types in SQL. We'll start by learning about ENUMs and ARRAYs, and then move on to Ranges and Nested Data. This section will give you the knowledge and skills needed to handle a variety of data types, enhancing your database design and management capabilities.
  • 5. Advanced query techniques: exploring OVER, JOINS, CASE and more in SQL
    32 Min
    Expand your querying capabilities by introducing advanced SQL techniques. You will explore the power of the OVER clause, dive deep into different types of JOINS, and learn to use CASE for conditional logic. With additional lessons on functions like COALESCE, CONCAT, and Recursive CTE, this section will elevate your SQL skills to a new level.
  • 6. Optimizing data structures: The art and science of data normalization in SQL
    9 Min
    Focus on optimizing data structures through Data Normalization. You'll learn about the principles of data normalization and their importance in creating efficient, reliable databases. This section will equip you with the knowledge to design and implement database schemas effectively.
  • 7. Performance and control: Mastering stored procedures, temporary tables, and control structures in SQL
    26 Min
    Introduction to performance and control features in SQL. We'll learn about stored procedures and user-defined functions, temporary tables, and materialized views. Plus, we'll discuss SQL transactions and control structures. By the end of this section, you'll have a deeper understanding of database performance and control mechanisms in SQL.
  • 8. Practical tasks
    11 Min
    A series of practical tasks that will help you reinforce what you have learned in the Advanced SQL for Data Engineers course
  • 9. Course exam
    35 Min

Free preview

Introduction to the course

1.1 Introduction to the course

1 min

Coure GitHub repository

1.2 Coure GitHub repository

1 min

Setting up the environment

1.3 Setting up the environment

3 min

An overview of relational databases

1.4 An overview of relational databases

3 min

DDL, DML, DQL, DCL

1.5 DDL, DML, DQL, DCL

3 min

SQL syntax

1.6 SQL syntax

3 min

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94%

of AI and data science graduates

successfully change

or advance their careers.

9 in 10

people walk away career-ready

with practical data and AI skills.

9 in 10

of our graduates landed a new AI & data job

after enrollment

ACCREDITED certificates

Craft a resume and LinkedIn profile you’re proud of—featuring certificates recognized by leading global institutions.

Earn CPE-accredited credentials that showcase your dedication, growth, and essential skills—the qualities employers value most.

  • Institute of Analytics
  • The Association of Data Scientists
  • E-Learning Quality Network
  • European Agency for Higher Education and Accreditation
  • Global Association of Online Trainers and Examiners
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How it WORKS

  • Lessons
  • Exercises
  • Projects
  • Practice Exams
  • AI Mock Interviews

Lessons

Learn through short, simple lessons—no prior experience in AI or data science needed.

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Exercises

Reinforce your learning with mini recaps, hands-on coding, flashcards, fill-in-the-blank activities, and other engaging exercises.

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Projects

Tackle real-world AI and data science projects—just like those faced by industry professionals every day.

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Practice Exams

Track your progress and solidify your knowledge with regular practice exams.

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AI Mock Interviews

Prep for interviews with real-world tasks, popular questions, and real-time feedback.

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Student REVIEWS

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