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DataCamp

DevOps Concepts

via DataCamp

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Overview

In this Introduction to DevOps, you’ll master the DevOps basics and learn the key concepts, tools, and techniques to improve productivity.

DevOps is all about driving high-quality software development productively and collaboratively. It is a mix of cultural philosophies, practices, and tools to deliver software in a better way. The course simplifies the complex modern software development environments and puts you in the driver's seat.

As you work through the course, you’ll explore the differences between DevOps, DataOps, and MLOps. In addition, you’ll cover project management methodologies, software architecture concepts, and Continuous Integration and Continuous Delivery (CI/CD).

Syllabus

  • Introduction to DevOps
    • This chapter will go through what DevOps is, discover its principles and see what benefits it brings. You will discover how it is applied to different kinds of software development. Lastly, you will look at the basics of project management to see different approaches and how they can power up DevOps to bring substantial advantages to organizations.
  • DevOps Architecture
    • This chapter introduces the main components of IT infrastructure, change management, and software architecture. You will see how different parts come together to compose online products, how they interact with each other, and how teams collaborate on the DevOps Change Management Model. You’ll explore the main elements of DevOps in detail.

      At the end of this chapter, you will be empowered to tackle some of the complex software engineering problems, like architectural design, and improve online products safely and quickly.
  • Implementation of DevOps for Data Engineering
    • Here, you will embark on a journey to navigate DevOps through the lens of a data engineer. You will explore what the DevOps architecture means from a Data Engineering standpoınt. Further, you will look at the main concepts related to Data Pipelines and how they are used in a microservices architecture.
      After learning about data pipelines, you will put your Data Scientist hat on and look at DevOps from a reporting perspective. Lastly, you will look at the tooling environment of DevOps and discuss the main tools used for DevOps.
  • Accurate, Predictive, and Unbiased Data With DevOps
    • In this final chapter, you will examine how DevOps helps ensure high data quality. Furthermore, you will look into quality and reliability in software. Last but not least, you will look at the cultural concepts enabling DevOps. Then, you will revamp everything you have learned and be fully equipped with the power of DevOps.

Taught by

Cem Sakarya

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