AI-Powered Software Testing: From Planning to Closure

Next-Gen STLC: Leverage LLMs & Prompt Engineering for End-to-End STLC phases


What you'll learn
Master the fundamentals of Generative AI, understanding the relationships between AI, ML, DL, and LLMs, and their applications in software testing.
Learn to optimize requirement analysis using AI, including refining requirements, creating traceability matrices, and identifying testable components.
Enhance test planning skills by using LLMs to define objectives, create detailed test plans, estimate efforts, and identify necessary resources.
Improve test case development through AI-assisted design, review, and generation of test data and scripts, increasing coverage and efficiency.
Master AI-driven test execution techniques, including root cause analysis, defect logging, retesting, and comprehensive reporting.
Utilize LLMs to streamline test closure activities, including metric analysis, trend identification, and preparation of final test result reports.

Requirements
Basic understanding of software testing concepts (optional)
A curious mindset and willingness to explore new technologies in software testing.

Description
Change the way you approach software testing with the power of Artificial Intelligence!
This comprehensive course equips you with the skills to
revolutionize
your testing process by leveraging the latest advancements in AI, specifically Large Language Models (LLMs).
What will you learn?
Master the Fundamentals:
Gain a solid understanding of Generative AI, Machine Learning, Deep Learning, and LLMs. Explore the capabilities and limitations of these technologies and how they can be applied to software testing.
Become an LLM Expert:
Deep dive into the world of LLMs like Gemini, ChatGPT, and Anthropic Claude. Learn how to leverage their power through
prompt engineering
. Craft effective prompts to achieve specific testing goals and extract valuable insights from these powerful tools.
Hands-on Practice Throughout:

This course isn't just theory!
Sections 4 through 9 take you through the entire Software Testing Life Cycle (STLC) with a
hands-on approach
. Learn how to apply AI and prompting techniques to each critical stage, from
requirement analysis
to
test closure
.
Here's a glimpse of what you'll experience:
Requirement Analysis:
Leverage AI's conversational capabilities to identify security vulnerabilities and refine requirements for a more robust testing strategy.
Test Planning:
Effortlessly estimate testing efforts, identify the right tools and environment needs, and define roles and responsibilities with the help of AI.
Test Case Design:
Craft high-quality test cases and scenarios for various functionalities, including API automation, using feature files and scripting techniques.
Test Environment Setup:
Learn to navigate cloud environments, identify cost-effective solutions, and troubleshoot errors to ensure a reliable testing infrastructure.
Test Execution & Closure:
Prioritize potential causes of test failures, log defects effectively, and analyze trends to optimize future testing cycles.
But that's not all!
We'll also delve into the ethical considerations of using AI in testing, covering data privacy, security, bias, and the importance of human oversight.
By the end of this course, you'll be able to:
Confidently leverage AI to streamline your software testing process.
Design and execute more effective test cases, improving software quality.
Increase testing efficiency and reduce overall testing time.
Communicate effectively with stakeholders and development teams.
Navigate the ethical considerations of AI in testing.
Ready to transform your software testing career? Enroll today!
Who this course is for:
Quality Assurance engineers and testers looking to enhance their skills with AI-driven techniques and stay ahead in their field.
Test Managers and Team Leads responsible for overseeing testing processes and want to implement cutting-edge AI solutions to improve efficiency and effectiveness.
Individuals from other IT backgrounds who are moving into software testing roles and want to enter the field with advanced, AI-powered skills.
Students and Fresh Graduates in Computer Science: Those who have a basic understanding of software development and testing, and want to specialize in AI-enhanced testing methodologies for a competitive edge in the job market.
Software Developers with Testing Responsibilities: Developers who are involved in testing activities and want to leverage AI to streamline their testing processes.

More Info