Applied Data Engineering Course (online)

  • Course level: Advanced  
Group Online Sessions (GMT) Duration Registration


Tuesdays 14h00 to 18h00 (GMT)
Fridays 14h00 to 18h00 (GMT)

36 Hours
From : 04/06/2024 01:00
To : 19/07/2024 23:59

Available Seats: 30
Registration Deadline
31/05/2024 23:59


A project-based data engineering course designed to teach fundamental concepts and techniques for automating data collection, preparation, and transforming it into clean data ready for in-depth analysis. This course is certified by EIT Tech Talent, European Union.


On successful completion of this course, trainees will be able to:

  1. Demonstrate a comprehensive understanding of essential data analytics topics, establishing a strong foundation for further exploration and application in the field of data engineering.

  2. Apply Data Warehousing Concepts to design and construct efficient data warehouses, including the ability to articulate and implement key architectural principles.

  3. Execute data sourcing and cleaning processes effectively, utilizing scripting techniques to ensure the accuracy and reliability of data integrated into the warehouse.

  4. Develop practical skills in ETL (Extract, Transform, Load) processes using industry-standard tools such as SSIS and Talend, enabling trainees to design and implement robust data pipelines.

  5. Implement advanced testing techniques in ETL processes, ensuring the quality and integrity of data transformations, and demonstrate proficiency in configuration management for maintaining the reliability of the data pipeline.


  1. Introduction to essential data analytics topics
  2. Data Warehousing Concepts
  3. Data Warehousing Architecture
  4. Data Warehousing Design: Building Blocks
  5. Data Sourcing
  6. Data Cleaning
  7. Script Requirements for Data Sourcing
  8. Metadata
  9. Data Integration
  10. File Validation
  11. The Staging Layer
  12. Business Validation Layer
  13. Data Warehouse Layer
  14. Developing ETL with SSIS
  15. Developing ETL with Talend
  16. Testing Techniques in ETL
  17. Mapping examples
  18. Audit, Balance and Control
  19. Configuration Management
  20. Implementing ChatGPT in Python
  21. Reviewing the techniques of Prompt Engineering and Generative AI
  22. Final Project: Applying Data Engineering techniques to  real datasets and building the required ETL pipeline

Registration fee :
€ 1700

Target audience

  • IT Administrators
  • Data Engineers
  • Data Center Staff and Administrations
  • Computer Science students and graduates
  • Engineering students and graduates


  • - Basic Programing skills
  • - SQL
  • - Essential skills in database design