BOOTCAMPS
Data Engineering
The Data Engineering Bootcamp is designed to equip you with the skills to handle large-scale data systems. You’ll learn how to design data architectures, create ETL (Extract, Transform, Load) pipelines, and work with cloud platforms to process and store data efficiently. This course prepares you for the challenges of managing data in today’s fast-paced, data-driven world.
Throughout the bootcamp, you’ll gain hands-on experience with industry-standard tools and frameworks like Python, SQL, PySpark, and Azure Data Tools. The program covers critical topics such as data pipeline design, data lake architecture, and real-time processing. You’ll also learn to work with Linux for command-line operations and server management, essential for modern data engineering workflows. Real-world projects and case studies will help you understand how to manage, optimize, and scale data pipelines for analytics and machine learning applications. Whether you’re a beginner or seeking to upskill, this bootcamp equips you with the knowledge and practical expertise for a successful career in data engineering.
Someone who completes this bootcamp can easily apply to junior data engineering job postings. In addition, we get to know our students closely throughout the bootcamp and create a roadmap for them. We guide them to develop both their technical and soft skills.
All courses are online and face to face. Before the course, students prepare weekly from the Learning Management System. After the course, homework and group work are done to fully understand and reinforce the subject. Thus, complete and permanent learning is ensured.
Key Points
- Comprehensive Curriculum – Learn data architecture, ETL, and big data technologies.
- Hands-On Projects – Build and manage real-world data pipelines.
- Microsoft Azure – Solve problems easily with cloud computing, an indispensable technology today.
- Industry Tools – Learn Python, SQL, and PySpark.
- Data-Driven Insights – Learn to interpret and communicate data effectively.
- Expert Guidance – Receive mentorship from experienced data professionals.
- Career Ready – Prepare for roles as a Data Engineer or related positions.
- Flexible Learning – Designed to fit your schedule and pace.
Course Lessons
Introduction to Data Engineering
Learn the fundamentals of data engineering, its critical role in the data ecosystem, and how it enables efficient data management and analytics. This course provides an overview of key concepts such as data pipelines, ETL processes, and data architecture. You will also explore the primary tools and platforms used in the field. By the end of this course, you’ll have a solid understanding of the foundational principles of data engineering and how they support modern data-driven decision-making.
Data Architecture and Modelling
Gain a comprehensive understanding of how to design robust data architectures, create optimized schemas, and model data for efficient storage, retrieval, and processing. This course covers key principles of database normalization, denormalization, and data modeling techniques for both relational and non-relational databases. You’ll learn how to design scalable data systems that support analytics and machine learning workflows while ensuring performance and reliability. Practical examples and case studies will help you apply these concepts to real-world scenarios, equipping you with the skills to tackle complex data engineering challenges.
Python
The Python module introduces participants to Python programming, covering essential topics such as data types, loops, functions, and file handling. The course also includes advanced topics like Object-Oriented Programming (OOP), enabling participants to design scalable and reusable code.
SQL
The SQL module equips participants with essential skills to work with relational databases. Topics include writing queries to retrieve, filter, and aggregate data, as well as managing database structures using concepts like joins, subqueries, and indexing. Participants will also learn how to analyze and manipulate large datasets efficiently, a critical skill for data engineering applications.
Azure Data Engineering
The Microsoft Azure Data Engineering module provides participants with a comprehensive understanding of cloud computing and its role in modern data engineering workflows. The course covers essential Azure services such as Azure Databricks, Azure Data Factory, Azure Data Lake Storage and Azure SQL Database. Participants will learn how to deploy, manage, and scale data solutions in the cloud, preparing them to work on real-world data engineering projects effectively.
Capstone Project
The Capstone Project allows participants to apply the skills and knowledge gained throughout the bootcamp to a real-world data engineering challenge. Students will work on a comprehensive project that involves designing and building data pipelines, implementing ETL processes, and optimizing data architectures for scalability and performance. They will also integrate tools such as SQL, Python, PySpark, and cloud platforms like Azure to manage and process large datasets efficiently. This hands-on, team-based project provides valuable experience in developing end-to-end data engineering solutions, preparing participants to tackle complex, real-world challenges in the field.
Individual Career Planning
As part of the bootcamp, each participant will receive personalized career planning to guide their professional journey. This includes advice on obtaining relevant certifications, identifying strengths and areas for improvement, and building a tailored roadmap for career success. Additionally, experts will conduct sessions on key topics such as crafting a compelling CV and cover letter, navigating the job application process, and mastering interview techniques, ensuring participants are well-prepared for their career transitions.