ARTIFICIAL INTELLIGENCE IN DATA ENGINEERING
In today’s data-driven world, organizations rely on efficient data systems to power innovation and decision-making. At Smart Data Warehouse Solutions Institute, our Foundational Data Engineering Program is designed to equip you with the basic skills to design, build, and optimize scalable data architectures. Through hands-on projects, expert mentorship, and industry-aligned modules, you’ll master data modeling, ETL processes, and cloud integration thereby preparing you to drive Business Intelligence and analytics in a rapidly evolving digital landscape.
DURATION
3 MONTHS
(Africa, Canada & USA)
AWARD
ADVANCED PROFESSIONAL CERTIFICATE
CLASSES
HYBRID
TUITION
NGN1,500,000
(Africa)
CAD 8,500
(Canada & USA)
Be in Demand with Our Professional Training
We’ve launched a new, Advanced Certification for professionals ready to move beyond traditional ETL and into the world of AI-powered Data Engineering. This program is a continuation of our ETL curriculum, designed for those who have completed our Professional Diploma I or II, or for highly self-directed learners with strong foundational skills. It’s not an entry-level course; rather, it’s a strategic leap into the future of intelligent data systems. This certification is designed to help you build intelligent systems, not just pipelines — and to do so with clarity, control, and confidence.
Techniques for powering LLM-driven insights and retrieval-augmented generation (RAG).
How to embed structured data warehouses (gold layers) into vector databases.
Progressive scenarios — from simple pipelines to advanced AI-integrated.
Data preparation strategies for structured, semi-structured, and unstructured formats architectures.
This certification is designed not just to help you learn how to build pipelines but also to build intelligent systems with clarity, control, and confidence.
WHAT YOU WILL LEARN
because tools are only as powerful as the problems they solve
Agile, Hybrid, and Data-specific workflows
How to design systems that scale.
With a focus on efficiency, safety, and security.
Because we don’t just train, we mentor.
WHO SHOULD APPLY
Graduates of Diploma I or II at Smart Data Warehouse Solutions Institute
.
Professionals with strong self-learning capacity and exposure to ETL workflows
INDIVIDUALS PLANNING TO WORK IN AI-INTEGRATED DATA ENVIRONMENTS
Frequently Asked Questions
Data Engineering focuses on designing, building, and maintaining the systems that collect, store, and process large volumes of data for analysis and decision-making.
Anyone with an interest in data, programming, or cloud technologies can join. A background in IT, computer science, or mathematics is an advantage but not required.
The Diploma in Data Engineering is a one-year intensive program, combining theory, hands-on labs, and real-world projects.
Students will gain practical experience with Python, SQL, Snowflake, Azure Data Factory, Databricks, Apache Spark, and Power BI.
Basic computer literacy is enough. The program starts with foundational modules before advancing to complex data engineering concepts.
Yes. Students will complete capstone projects and case studies that simulate real industry challenges in data pipeline design and automation.
Graduates can work as Data Engineers, Cloud Engineers, ETL Developers, Database Administrators, or BI Engineers in diverse industries.
The program offers both on-site and hybrid learning options, giving flexibility to students based on their schedules.
Yes, successful students will be awarded a Foundation in Diploma in Data Engineering from Smart Data Warehouse Solutions Institute.
You can apply through our official website or visit our admissions office to complete your registration and secure your spot.
Every Expert Starts with the Right Training.
At Smart Data Warehouse Solutions Institute, we don’t just teach Data Engineering — we empower innovators to design scalable data systems that power intelligent decision-making and business transformation.
Join us today and turn your passion for data into a dynamic career in cloud computing, analytics, and modern data architecture.