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Regular version of the site
Bachelor 2021/2022

DevOps

Area of studies: Applied Mathematics and Information Science
When: 4 year, 2, 3 module
Mode of studies: distance learning
Open to: students of all HSE University campuses
Instructors: Pavel Akhtyamov
Language: English
ECTS credits: 6

Course Syllabus

Abstract

DevOps is a set of software development practices that combine software development (Dev) and information-technology operations (Ops) to shorten the systems development life cycle, while frequently delivering features, fixes, and updates in close alignment with the given business objectives. Graduates often lack practical skills and experience required for professional success in the IT industry. The DevOps course will give you an opportunity to develop and polish relevant skills needed for large-scale complex projects, including system design, system deployment, support, version control systems, virtualization, etc. This valuable hands-on experience will allow you to start working on your own industrial-level projects and effectively collaborate with your team members if you are hired by an IT company. During the course, you will have an opportunity to solve many practical problems focused on various aspects of a product life cycle.
Learning Objectives

Learning Objectives

  • To master the basic tools to develop and maintain software service lifecycle
Expected Learning Outcomes

Expected Learning Outcomes

  • To know how to deploy cloud services
  • To understand Git and build automation systems
  • To understand the concept of CI / CD
Course Contents

Course Contents

  • Introduction
  • Virtualization and Cloud
  • IaC and Configuration Management
  • Containerization
  • CI/CD
Assessment Elements

Assessment Elements

  • non-blocking HW1
  • non-blocking HW2
  • non-blocking HW3
Interim Assessment

Interim Assessment

  • 2021/2022 2nd module
  • 2021/2022 3rd module
    0.33 * HW1 + 0.33 * HW2 + 0.34 * HW3
Bibliography

Bibliography

Recommended Core Bibliography

  • Christopher M. Bishop. (n.d.). Australian National University Pattern Recognition and Machine Learning. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.EBA0C705

Recommended Additional Bibliography

  • M Narasimha Murty, & V Susheela Devi. (2015). Introduction To Pattern Recognition And Machine Learning. World Scientific.