AI for Testing and Practical Applications - Bespoke

AI for Testing and Practical Applications

Course Outline

2 days | 8 hrs per day (including breaks)

Day 1: Introduction to AI, NLP and Generative AI

• Session 1: Introduction to AI
  • Overview of AI and its impact across industries.
  • Understanding the basics of machine learning and deep learning.
  • Discussion on the evolution of AI technologies and their current capabilities.
• Session 2: Intro to Natural Language Processing (NLP)
  • Foundational concepts in NLP.
  • Introduction to text preprocessing techniques.
  • Overview of traditional NLP models and algorithms.
• Session 3: Advanced NLP - Transformers and Transfer Learning
  • Architecture and workings of Transformer models.
  • Concepts of transfer learning and fine-tuning in the context of NLP.
• Session 4: Introduction to Generative AI and ChatGPT
  • Understanding generative AI and its applications.
  • Exploring the architecture and capabilities of ChatGPT.
  • Understanding privacy issues

Day 2: Generative AI for Testing

• Session 5: Foundations of Retrieval Augmented Generation (RAG)
  • The concept of RAG and how it enhances generative models.
  • Integrating retrieval into generative models for better context understanding.
  • Workshop: Implementing a basic RAG model for information retrieval.
• Session 6: GPT + RAG for Insights from Unstructured Data
  • Techniques for extracting insights from unstructured data using GPT and RAG.
  • Case study: Analysis of textual data to gather business intelligence.
• Session 7: GPT for Insights from Structured Data
  • Applying GPT models to structured data analysis.
  • Techniques for transforming structured data into a format suitable for GPT.
• Session 8: Generating Test Cases from Documents and Sheets
  • Strategies for generating test cases from unstructured documents and structured sheets.
  • Practical workshop: Using AI to automate test case generation from product specifications and requirement documents.