Quantum starts a course in partnership with the University of Warsaw

Discovering the domain of Data Engineering is a journey that knows no boundaries. Our course, arranged in partnership with the University of Warsaw, will give students all the necessary information to start.

This program centers on bridging the gap between industry and traditional academia and sharing methods and tools proven effective in today’s dynamic Big Data landscape.

At Quantum, we focus on enhancing professional skills, sharing knowledge, and fostering a solid software community.

We’re totally into giving students opportunities to work on meaningful projects and improve using the latest technologies to invest in the future and support the next big thinkers.

About the Course

The course’s main objective is to introduce students to the basic principles of most data-processing tasks and the mechanics of modern data engineering tools.

Description:

This course will start by demystifying data engineering, setting it apart from systems like personal blogs or e-market platforms. We delve into the significance of file formats, break down the core concepts of databases, and explore data storage methods. Learn how to execute processing tasks within data pipelines, orchestrate independent tasks, and integrate elements using tools like queues.

Learning outcomes:

Students will grasp the basics of data processing tasks and familiarize themselves with the mechanics of modern tools.

Duration:

60 hours.

Study format:

Lectures, hands-on labs, individual assignments, and a final project.

Our lecturer:

Yura Braiko —  a Data Engineer at Quantum Inc. with 10 years of experience in IT, including 4+ in Data Engineering. He is working on various projects in the area of processing data from financial institutions, building knowledge graphs, and analyzing sensor information. Yura is open to live communication, eager to share knowledge, and help students with course assignments or any engineering task they encounter.

Course program:

— Data processing pipeline overview.

— Raw data collection and storage.

— Data processing, cleaning, and storage of processed data.

— Scaling tools for data processing systems.

Throughout this course, students will:

— Comprehend fundamental data processing principles.

— Gain insights into modern tool mechanics.

— Learn best practices irrespective of the technology stack.

— Engage in practical tasks useful for novices and experienced professionals.

— Receive valuable links to blogs and forums.

Requirements for the students: 

— Competence in the basics of the programming language or good knowledge of at least one programming language: Python / Java / R.

— Competence in the basic operation of the Unix / shell.

— Competence in the Docker.