5 days





Course features:


Lab Setup:

Learning Path

  • Overview of Python language features and syntax
  • Data types, variables, and operators
  • Control structures: if statements, loops
  • Defining and calling functions
  • Working with modules and packages
  • Introduction to Python standard library modules relevant to automation
  • Reading from and writing to files
  • Exception handling with try-except blocks
  • Best practices for error handling in automation scripts
  • Writing Python scripts to perform common automation tasks
  • Practice exercises covering file manipulation, text processing, and basic system administration tasks
  • Overview of Ansible and its architecture
  • Ansible components: control node, managed nodes, inventories
  • Installing Ansible and configuring the control node
  • Understanding Ansible playbooks
  • Writing YAML syntax for defining tasks
  • Executing playbooks to perform configuration management tasks
  • Managing inventories in Ansible
  • Working with dynamic inventories
  • Using variables for configuration management
  • Overview of Ansible modules
  • Commonly used modules for system administration tasks
  • Hands-on exercises using Ansible modules for package management, file operations, and user management
  • K-Means clustering
  • Hierarchical Clustering
  • Recommender System and Association
  • Project case studies: Classification of drugs, prediction of heart disease, Association of Ingredients in Drug, Liver Disease Prediction
  • Organizing playbooks with roles
  • Structure and conventions of Ansible roles
  • Writing reusable and modular playbooks using roles
  • Integrating Python scripts with Ansible playbooks
  • Calling Python functions from Ansible tasks
  • Passing data between Ansible and Python
  • Generating dynamic inventories using Python scripts
  • Integration with cloud providers and other infrastructure platforms
  • Automating inventory updates and maintenance
  • Custom Ansible modules in Python
  • Ansible callback plugins for custom reporting and logging
  • Hands-on exercises integrating custom Python code with Ansible automation tasks
  • Best practices for writing efficient and maintainable playbooks
  • Organizing code with roles, tasks, and templates
  • Using Ansible Galaxy for sharing and reusing roles
  • Performance optimization tips for Ansible playbooks
  • Reducing playbook execution time with strategies like async and poll
  • Profiling and troubleshooting playbook performance issues
  • Testing Ansible playbooks with Ansible-lint and other testing tools
  • Integration with continuous integration (CI) systems like Jenkins
  • Automated testing and deployment pipelines for Ansible projects
  • Reviewing real-world examples of Ansible automation projects
  • Analyzing use cases and architectures
  • Q&A and open discussion on challenges and solutions
  • Participants work on a comprehensive automation project combining Python programming with Ansible orchestration
  • Project scope includes infrastructure provisioning, configuration management, and deployment automation
  • Participants present their capstone projects to the class and instructors
  • Projects are evaluated based on completeness, effectiveness, and adherence to best practices
  • Feedback provided to participants for further improvement and learning
  • Recap of key concepts and takeaways from the bootcamp
  • Distribution of course completion certificates to participants