Foundations and Modern Practices of Data and AI Engineering

Aalto University via Aalto University Executive Education Professional Certificate

Go to class Write review

The Foundations and Modern Practices of Data and AI Engineering program equips participants with the essential knowledge and hands-on skills needed to design and maintain scalable, high-performance data pipelines. For organizations, this translates to more reliable data, streamlined workflows through automation, and advanced analytics capabilities that enable smarter, data-driven decision-making. For professionals, it provides an opportunity to gain in-demand expertise while working directly with modern data engineering tools and technologies. In this program, you’ll learn to manage the seamless flow of data across diverse systems. Through practical, real-world exercises, you will explore a variety of data storage solutions—from traditional relational databases to modern unstructured data lakes. Beyond theoretical concepts, this program delivers actionable skills, preparing you to confidently build, maintain, and optimize sustainable data infrastructures for today’s complex, data-driven environments.

Syllabus

Learning Outcomes

In today’s data-driven economy, organizations that can effectively collect, process, and analyze information gain a clear competitive edge. If your goal is to design robust data infrastructure, build scalable data solutions, or manage large and complex datasets, this program will equip you with the practical skills to do so. The applications of these capabilities are virtually limitless.

In this program you will:

Grasp the fundamental principles and core concepts of data engineering
Build a solid understanding of ETL (Extract, Transform, Load) processes
Develop the ability to design, implement, and optimize ETL workflows
Gain hands-on experience with industry-standard data engineering tools and technologies
Learn to design, construct, and maintain robust, scalable data pipelines
Understand the importance of data quality, governance, and data lineage
Acquire skills to work effectively with a variety of data storage architectures
Prepare to support data warehouses, machine learning workflows, and AI-driven applications

Content and Schedule

This program provides a comprehensive introduction to the key principles of data engineering, including Extract, Transform, Load (ETL) processes, data storage architectures, and the design of scalable data pipelines. Participants will gain practical, hands-on experience using modern data technologies and tools, while learning how to develop and maintain data systems that support advanced analytics, artificial intelligence, and machine learning initiatives.

The program is arranged as a two-day module in April 14-15, 2026, including a reflective pre-assignment. The on-site days are in Aalto EE Töölö, Runeberginkatu 14-16, 00100 Helsinki.

We offer a group discount when two or more people from your organization participate in the training:

5 or more participants: 25% discount
4 participants: 20% discount
3 participants: 15% discount

The discount is calculated directly at the checkout when the required number of seats has been added to the cart.

For Whom?

This course is designed for individuals with a foundational understanding of software development and a passion for learning. It begins with the core concepts and gradually advances your skills, guiding you toward becoming proficient in data engineering.

Whether you’re an analyst familiar with SQL, a programmer who automates workflows, or a developer interested in expanding into data engineering, this program is an ideal fit. If you already have experience in these areas, you possess the essential foundation needed to excel in data engineering projects.

By completing this program, you’ll not only enhance your technical expertise but also play a key role in building powerful, data-driven systems that improve efficiency and drive organizational success.