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Data Engineering Course

Schedule:

Duration of paid internship (5 days/week, 8 hours/day):
2,5 months

Course description

The Data Engineering course is designed for those interested in a career in data. This course will teach the fundamentals of data engineering related to building data pipelines using Python, SQL, NoSQL, and other modern technologies.

You will get acquainted with the Data Engineering ecosystem, data integration pipelines, and data repositories within the course. You will study relational and non-relational databases, learn what data warehouses are, and also be able to store and process large amounts of information.

As part of the course, you will be able to:

  • Understand what data engineering is and what a modern data ecosystem looks like.
  • Apply into practice the basics of Python programming and various ways of processing data using basic constructs, collections, Pandas, etc.
  • Learn databases, including database design, creating tables, using, and working with constraints, and much more.

Projects

Throughout the education process, students will work with projects that cover the material studied during the course, which allows them to consolidate the knowledge gained in practice. The final stage of the Data Engineering course - final project development. You will be able to comprehensively collect all the knowledge gained during the course and apply it in practice using real cases and working with a real team. All cases include solving a real problem using the knowledge and experience you have acquired during the training. In addition, the final project will allow your mentors and colleagues to validate and approve your knowledge.

Evaluation

During the educational process, students will complete homework and projects. Based on this, experts will assess the student's practical skills and knowledge, as well as the level of individual work. The results of the final project will be evaluated by mentors, they will conduct a comprehensive assessment of approaches and artifacts.

Course program

1.
Git

Git

Linux

Docker

CI/CD

Data-driven/product mindset

Data Analysis

Python

Data Engineering

Airflow

AWS

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