Course Description
Python is an interpreted, object-oriented, high-level language that empowers you to automate your work so it can be completed predictably and accurately. This freely available language is installed on all major platforms without a charge. Given Python’s vast libraries, you’ll have a head start programming most tasks. Be it system admins, network, cloud, or storage engineers, all lessons in our courseware are highly relevant for scripting within the workplace, including data retrieval and storage from the local system, working with RESTful APIs, and decoding JSON. The class is a combination of live instructor demos and hands-on labs.
Target Student
- This course is an appropriate introduction to students of any background looking to get started with Python.
- System Administrators
- Network Administrators and Engineers
- DevOps Engineers
- Management, Directors, VPs
Course Objectives
- Current Python3 Standard Library
- Popular 3rd party libraries
- Version control with git
- Git integration with popular SCM (GitHub)
- Parsing and building files
- Pull JSON from API queries
- Manipulate Excel and other popular formats with pandas dataframes
- Building feature-rich charts and graphs
- Searching with Regular Expressions (regex)
- Best practice techniques
- AI LLM prompt engineering for Python snippets and jumpstarting solutions
Course Content
AI LLM Toolkit
- Lecture + Lab: Large Language Model toolkit for AI Solution Assistance
Software Control Management
- Lecture + Lab: SCM Option #1 - GitHub
- Lecture + Lab: SCM Option #2 - GitLab
Basics
- Lecture + Lab: Installing Python
- Lecture: Python Basics
- Lecture + Lab: The Shebang Line and File Permissions
- Lecture + Lab: The Standard Library, functions, and print()
- Lecture + Lab: Collecting user input()
Common Objects
- Lecture: Python Lists
- Lecture + Lab: Working with Lists
- Lecture + Lab: List Objects and Methods
- Lecture + Lab: Slicing complex lists (lists within lists)
- Lecture: Python Dictionaries
- Lecture + Lab: Python Dictionaries
- Lecture + Lab: Getting dir(obj) help() and pydoc
- Lecture: Python Strings
- Lecture + Lab: String Methods
Interacting with the OS
- Lecture + Lab: Copying Files and Folders
- Lecture + Lab: Moving and Renaming Files and Folders
Conditionals
- Lecture: Conditionals
- Lecture + Lab: Testing if conditionals
- Lecture + Lab: IPv4 Testing with if
- Challenge: Writing your own if-logic script
- Lecture + Lab: Using while, if, elif, else (Monty Python)
- Lecture + Lab: Debugging and Troubleshooting while, if, elif, else
Loops
- Lecture + Lab: Introduction to looping
- Lecture + Lab: Looping with for
- Lecture + Lab: Using for, range(), and with
Working with Files
- Lecture: Reading and Writing to Files
- Lecture + Lab: Parsing Log Files
- Lecture + Lab: Creating Output Files from Data Sets
- Lecture + Lab: Read from Files
- Lecture + Lab: Archive with zipfile
Beyond Basics
- Lecture + Lab: Creating Functions
- Lecture + Lab: pip, import, and PyPi Packages to Know
- Lecture + Lab: Exploring Network Interfaces
- Lecture + Lab: Defining Functions
- Lecture + Lab: Scripting Commands with Python
- Lecture + Lab: try and except
Working with Data Sets
- Lecture + Lab: Producing Graphs and Charts
- Lecture + Lab: os.walk() the Directory Tree
- Lecture + Lab: Excel JSON and CSV - Intro to Pandas
- Lecture: Converting JSON to Python Data Types
- Lecture + Lab: Python, APIs, and JSON
- Lecture + Lab: requests library - Open APIs
Regular Expressions
- Lecture + Lab: Searching with Regular Expressions
- Lecture + Lab: Use RegEx to Search Text
Testing and Tools
- Lecture + Lab: Best Practice and pylint
- Lecture + Lab: Testing code with pytest
- Lecture + Lab: Packaging Python Projects
Classes and Objects
- Lecture + Lab: Creating Classes
- Lecture + Lab: Inheritance
- Lecture + Lab: Using Classes
Self-Study Opportunities
- Lecture + Lab: Running Python Scripts with Crontab
- Lecture + Lab: Argument Parsing
- Lecture + Lab: Unpacking Arguments
- Lecture + Lab: Automating SMTP and Extended SMTP
- Lecture + Lab: XML Parsing with ElementTree
- Lecture + Lab: Timestamping - import time datetime
