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Simplified AI Workshop

The objective of this workshop is to help Quality Engineering professionals understand Generative AI fundamentals and explore practical AI-driven testing use cases across the software testing lifecycle. Participants will learn how to evaluate AI-powered QE tools, apply AI for test automation and defect analysis, and gain hands-on exposure to prompt engineering, agent-based workflows, and AI-assisted automation to improve testing efficiency, quality, and delivery speed.

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Course Includes

  • 8 Hrs of Session
  • 24/7 Lifetime Support
  • One-on-one doubt clearing
  • Hands-On Driven
  • Certification Based Curriculum
  • Career path guidance
  • Real Time Users
  • Flexible

Why Choose TM SQUARE?

We have delivered the AI Workshop program to over 1200+ professionals, focusing on practical, application-oriented learning. Our sessions are designed to be engaging, activity-based, and tailored to real-world challenges. With an average participant rating of 4.4/5, the program is consistently recognised for its clarity, relevance, and impact. Join this course to experience the expertise of our professional instructors and best experience of learning concepts.

 

Course Overview

This AI Workshop for Quality Engineering Professionals is a practical, beginner-friendly program designed to help QE teams understand and apply Generative AI in modern testing and engineering workflows. The workshop covers AI fundamentals, LLMs, prompt engineering, AI agents, RAG, MCP, and real-world QE use cases including test design, automation, defect analysis, reporting, and documentation.

Through concept sessions, live demonstrations, hands-on exercises, and interactive discussions, participants will also learn how to evaluate AI tools and explore agent-driven workflows using PostQode Agents across Web and API scenarios. By the end of the workshop, participants will gain practical knowledge and actionable insights to effectively adopt AI within QE teams and engineering organizations.

 

Target Audience

• Quality Engineers
• Test Automation Engineers
• QE Leads and Managers
• Engineering Teams exploring AI adoption
• Professionals involved in SDLC and QA transformation initiatives

Workshop Format

• Concept Sessions
• Live Demonstrations
• Guided Hands-on Exercises
• Interactive Discussions

Pre-requisites

No prior AI experience is required. Participants are expected to have at least 3 years of Quality Engineering experience.

 

Expected Outcomes

By the end of the workshop, participants will:
• Understand the fundamentals of Generative AI and LLMs
• Explore practical AI use cases across QE workflows
• Learn how to evaluate AI tools and platforms
• Gain exposure to AI agents and agentic workflows
• Understand practical adoption approaches for AI in QE teams

 

Course Outline

What is your return policy?

We offer a 30-day return policy from the date of purchase.

Do I need a receipt to return an item?

Yes, a valid receipt or proof of purchase is required.

Can I return online purchases in store?

Yes, online purchases can be returned in any of our physical stores.

How long does shipping take?

Standard shipping typically takes 3–5 business days.

Do you ship internationally?

Yes, we ship to most countries worldwide. Additional charges may apply.

Which countries are excluded?

We currently do not ship to embargoed countries or regions with postal restrictions.

Section 1: Fundamentals of Generative AI

An introduction to Generative AI concepts and how GenAI differs from traditional AI systems
Modern AI systems including LLMs, prompts, tokens, context windows, embeddings, agents, MCP, RAG, Knowledge Graphs, grounding, hallucinations, workflows, and skills.
How LLMs work conceptually, prompt engineering practices, and understanding token usage and model costs.
Section 2: QE Use Cases with AI

Application of AI across the Quality Engineering lifecycle.
Topics include requirement analysis, gap analysis, story interpretation, test design, automation, bug analysis, reporting, observability, documentation, and related QE workflows
Practical demonstrations and hands-on exercises across different QE use cases
Section 3: Evaluating AI Tools

Evaluate AI tools and platforms across areas such as general capability, LLM selection, input/output quality, cost, governance, and control.
Practical considerations while selecting AI solutions for engineering teams and enterprise environments
Section 4: Hands-on with AI Agents

Hands-on sessions using PostQode Agents across API, Web, and Agent workflows.
Practical exercises on working with agents, MCP connectivity, and agent-driven workflows
Participants will explore AI-assisted execution flows and agent orchestration through guided activities
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