PYTHON FOR TEST AUTOMATION WITH AI-TOOLS
Place: Online
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Lena Bernhardsson – SE, NO
+46 (0) 40 59 22 09
lena.bernhardsson@nohau.se
Heidi Lehtomäki – Finland
phone: +358 40 196 0142
heidi.lehtomaki@nohau.fi
Flemming Jensen – Denmark
Phone: +45 44 52 16 60
fkj@nohau.dk
Python for Test Automation with AI-Tools & ChatGPT (Part 2)
This course is designed for developers, testers, and QA engineers who are responsible for creating and maintaining automated test suites using Python. Throughout the program, participants will learn the fundamentals of the Python language, essential Python libraries and test frameworks, and the ability to write unit tests and integration tests. In addition, the course offers an overview of AI tools and their application in completing exercises more efficiently than traditional methods. By the end of the course, participants will possess the necessary Python skills to create sophisticated and high-quality Python programs with the aid of AI-tools. This course presents a unique opportunity for individuals seeking to enhance their Python proficiency and explore the potential of AI in test automation.
Course Overview:
- Setting up a Python development environment
- Overview of Python Language fundamentals
- Python Standard Library
- The Most Popular Python third-party libraries
- Python Test Frameworks:
- Unit Testing (pytest)
- Property-Based Testing (hypothesis)
- Mutation Testing (cosmic-ray, mutmut)
- Behavior Driven Testing (behave)
- Keyword & Data Driven Testing (Robot Framework)
- Leveraging AI-Tools for Test Automation
- Introduction to Large Language Models (LLM) and Natural Language Processing (NLP)
- ChatGPT and alternative solutions
Training Format:
Instructor-led online training Duration: 3 days, 8 hours per day, totally 24 hours In the practical exercises, you use your own computers. Before the course, we will send instructions for installing the necessary software.
Instructor:
Our instructor, Miguel Miranda, has more than 20 years of experience as a software consultant specializing in Python and other programming languages. He has considerable experience in using AI-based tools for software development and process automation.
Course Overview: Python for Test Automation with AI-Tools & ChatGPT
Module 1 – Python Language
- Introduction
- Python Implementations
- Python 3
- Coding Style Guidelines
- Python Package Management
- Python Virtual Environments
- Python Development Environment
Module 2 – Python Language
- Python Language:
- Keywords
- Operators
- Basic Data Types
- Python Built-in Functions
- Functions, Classes, Modules and Packages
- Lambda functions
- List Comprehensions
- Generators
- Decorators
- Data Classes
Module 3 – Python 3 Standard Library
- Session 1: Runtime Features
- Session 2: Application Building Blocks
- Session 3: The File System
- Session 4: Text & Regular Expressions
- Session 5: Dates and Times
- Session 6: Data Persistence and Exchange
- Session 7: Data Compression and Archiving
- Session 8: Cryptography
Module 4 – Python 3 Standard Library
- Session 9: Mathematics & Data Analysis
- Session 10: Concurrency with Processes
- Session 11: Networking, Internet & Web Services
- Session 12: GUI Frameworks
Module 5 – Python Test Frameworks
Unit & Module Testing
- Unit Testing (pytest)
- Property-Based Testing (hypothesis)
- Mutation Testing (mutmut)
Module 6 – Python Test Frameworks
Integration, System & Acceptance Testing
- Behavior Driven Testing (behave)
- Keyword & Data-Driven Testing (Robot Framework)
Module 7 – Leveraging AI-Tools for Test Automation
Introduction to Large Language Models (LLM) and Natural Language Processing (NLP)
- ChatGPT, LLaMA, spaCy
Using Commercial & Open-Source AI Models
- Code & Test Generation
- Code Reviews
- Test Data Generation