08.04.2025
2 min
1030
This article brings together a selection of proven DevOps tools that help you master practical skills and work with real-world environments. The first part discusses services and labs that allow you to practice in a safe environment and build your path in DevOps more confidently. The article will be useful for those who want to understand the tools that simplify learning, preparing for work, or moving to a new level in the profession.
In this exercise, you practice working with NumPy by performing basic mathematical operations and calculations. The material helps you better understand arrays and apply them in practical problems.
This module introduces you to the basics of Git setup and working with GitHub. You will learn how to configure it, save changes, and create an environment for convenient teamwork on code.
This lab covers working with accounts in Linux. You will learn how to create, modify, and delete users, manage their permissions, and maintain order in the system.
The material introduces the simplest actions in Python: inputting data, outputting results, and working with variables. This is the first step towards creating interactive programs.
Here you will learn about Python’s conditional statements and how to control program logic. The lab demonstrates how to change the behavior of your code based on different conditions, making your program a little more flexible.
The lab explains how to work with classes and objects in Python. You will understand the principles of creating structured programs and applying an object-oriented approach.
This module shows you how to properly comment in Python. You’ll learn about single-line and multi-line comments, and how to make your code more understandable to others.
This course covers the basic Python data structures: lists, tuples, dictionaries, and sets. You will learn how to store, organize, and manipulate information efficiently.
Here you will learn how to create and use functions in Python. The module explains the structure, parameters, and return values, forming the foundation for building more complex programs.
The material focuses on working with conditional operators. You will learn about logical checks and performing different actions depending on the results of calculating conditions.
The lab introduces the IPython environment, its interactive capabilities, command history, and advanced tools for data exploration and rapid code testing.
In this module, you will learn Python’s mathematical operators and shorthand assignment, which will help you write shorter and more efficient code when performing calculations.
This article explains type conversions in Python. You will learn how to change data formats, combine different types, and check the correctness of calculations in programs.
Here you will use NumPy to perform statistical analysis on sets of values. The lab demonstrates basic computational techniques and builds a practical understanding of numerical operations.
In this task, you will learn how to delete and move files in Linux. The material trains working with the file system and basic administration skills in a command-line environment.
