Generative AI & LLM Testing with Prompt Engineering for Production : AI Reliability & Behavior Engineering – Live Training
(Generative AI & LLM Testing with Prompt Engineering, AI Evaluation, Hallucination Detection, Bias & Safety Testing, AI Reliability Engineering, and real-world industry projects)
As Generative AI systems become a critical part of modern products and enterprise applications, the challenge is no longer limited to building AI solutions — it is about ensuring they are reliable, safe, accurate, and production-ready. This program is specifically designed to bridge the gap between AI development and AI reliability engineering.
Unlike traditional QA or prompt engineering courses, this training focuses on testing, evaluating, and validating AI behavior in real-world production environments. Participants will learn practical frameworks, prompt testing strategies, adversarial testing techniques, safety evaluation methods, and AI quality assessment approaches used to analyze Large Language Models (LLMs) and conversational AI systems.
Through hands-on exercises, real-world scenarios, and industry-oriented projects, learners will gain the ability to identify hallucinations, bias, safety risks, prompt injection vulnerabilities, and conversational failures in GenAI applications. The course emphasizes structured evaluation methodologies such as R.A.I.N+ and B.R.A.I.N+ to measure AI performance across multiple dimensions.
By the end of the program, participants will be able to think beyond traditional software testing and confidently perform the role of an AI Reliability & Behavior Engineer, responsible for ensuring trust, robustness, safety, and high-quality AI experiences at scale.
About the Instructor:
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Sitara is a skilled professional with 9+ years of experience in Software Testing, Chatbot Quality Assurance, and Generative AI Testing. She has worked on testing and validating AI-powered applications, focusing on improving the reliability, safety, and performance of enterprise AI systems. Her expertise includes LLM Testing, Prompt Engineering, AI Behavior Analysis, Hallucination Detection, and Conversational AI Validation across real-world business use cases. She has hands-on experience in advanced areas such as Prompt Injection Testing, Jailbreak Testing, Bias & Fairness Evaluation, Multi-turn Conversation Testing, and AI Reliability Engineering. Her strong understanding of AI evaluation frameworks and GenAI testing methodologies helps learners gain practical exposure to real-time AI quality assurance and production readiness strategies. As a passionate trainer and mentor, she has successfully trained 200+ students and working professionals in areas related to Software Testing, AI Testing, and Generative AI Quality Engineering. Her training approach focuses on practical implementation, real-world scenarios, and industry-oriented learning, helping participants build confidence in testing and evaluating modern AI systems effectively. |
Sample Videos:
Generative AI & LLM Testing with Prompt Engineering for Production : AI Reliability & Behavior Engineering – Live Training Demo Video
Generative AI & LLM Testing with Prompt Engineering for Production : AI Reliability & Behavior Engineering – Live Training Day 1 Video
Generative AI & LLM Testing with Prompt Engineering for Production : AI Reliability & Behavior Engineering – Live Training Day 2 Video
Live Sessions Price:
For LIVE sessions – Offer price after discount is 300 USD 259 109 USD Or USD13000 INR 12900 INR 8900 Rupees
OR
Free Day 1 On:
Indian Timings: 15th June@ 9 PM – 10 PM (IST)/
U.S Timings: 15th June @ 11:30 AM – 12:30 PM (EST)/
U.K Timings: 15th June @ 4:30 PM – 5:30 PM (BST)
Day 1 Class Schedule:
For Participants in India: Monday to Friday @ 9 PM – 10 PM (IST)
For Participants in the US: Monday to Friday @ 11:30 AM – 12:30 PM (EST)
For Participants in the UK: Monday to Friday @ 4:30 PM – 5:30 PM (BST)
What Our Students Say About Sitara:
| The training was highly interactive and industry-focused. I especially liked the sessions on Prompt Engineering, AI Reliability Engineering, and multi-turn conversation testing. The hands-on approach made the learning experience excellent. – Ambika
Excellent training on Generative AI Testing with practical real-time examples, clear explanations, and strong industry-focused learning. – Mahi Sitara madam has strong knowledge in GenAI Testing and Conversational AI Validation. Her explanations on AI safety, bias testing, and jailbreak scenarios were very clear and easy to understand, even for beginners. – Emily Sitara training on Generative AI Testing was highly practical and easy to understand. The sessions on Prompt Engineering, AI Evaluation, and Hallucination Testing were explained with real-time examples. Her teaching style and industry-oriented approach helped me gain confidence in testing AI-powered applications. This course is very useful for anyone interested in AI Testing and AI Reliability Engineering.- Ravindra The course content, practical examples, and trainer support were excellent. I gained confidence in testing AI chatbots and LLM-based applications. – Jessica |
Salient Features:
- 40 Hours of Live Training along with recorded videos
- Lifetime access to the recorded videos
- Course Completion Certificate
Who can enroll for this course?
- Software Test Engineers & QA Professionals looking to transition into AI Testing
- Automation Testers interested in GenAI Validation and Prompt Testing
- SDET Engineers working on AI-Powered Applications
- AI/ML Engineers who want to improve Model Evaluation and AI Reliability
- Developers building applications using LLMs and Generative AI Tools
- Product Managers managing AI-Based Products and Chatbot Platforms
- Cybersecurity Professionals interested in Prompt Injection, Jailbreak Testing, and AI Security
- Business Analysts & Solution Architects involved in Enterprise AI Adoption
- Freshers & Students aspiring to build careers in AI Testing and AI Reliability Engineering
- Anyone interested in learning Hallucination Testing, Bias Detection, Safety Evaluation, and Production Readiness Audits for Generative AI Systems
What will I learn by the end of this course?
- Design a structured testing strategy for GenAI systems
- Evaluate AI outputs across accuracy, safety, and usability
- Identify and analyze:
- Hallucinations
- Bias and unsafe responses
- Context failures
- Perform adversarial testing, including prompt injection and jailbreak attempts
- Build and apply evaluation scorecards and testing frameworks
- Conduct a Production Readiness Audit for AI systems
- Think and operate like an AI Reliability & Behavior Engineer
Course Syllabus:
Module 1: Foundations & Mental Models (4 Hours)
This module sets the stage by building a clear understanding of how Generative AI systems work — without going too deep into theory.
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- What makes GenAI different from traditional AI systems
- How LLMs generate responses (in simple terms)
- Understanding tokens, prompts, and variability
- Why GenAI systems fail in real-world scenarios
Learning Focus: Participants begin to see AI systems as probabilistic and imperfect, rather than deterministic tools.
Module 2: The GenAI Testing Mindset (4 Hours)
This module shifts the learner’s thinking from traditional QA approaches to AI-specific evaluation.
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- Why pass/fail testing doesn’t work for GenAI
- Behavior vs correctness vs usefulness
- Subjectivity in AI evaluation
- Introduction to the B.R.A.I.N+ framework
Learning Focus: Understanding that testing GenAI is about judgment, context, and quality — not just correctness.
Module 3: Prompt Engineering for Testing (5 Hours)
Rather than teaching prompt engineering for building, this module focuses on using prompts to test and break systems.
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- Structuring prompts for evaluation
- Role-based prompting
- Prompt variations and fuzzing
- Ambiguity and edge-case prompting
- Adversarial prompt design
Learning Focus: Participants learn how to probe weaknesses in AI systems intentionally.
Module 4: Deep Dive into B.R.A.I.N+ (6 Hours)
This is the core of the program, where each dimension of AI behavior is explored in depth.
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- Accuracy and factual validation
- Safety and harmful response detection
- Bias and fairness evaluation
- Conversational quality and tone
- Context retention and multi-turn behavior
- Handling edge cases and ambiguity
Learning Focus: Learners develop a structured way to analyze and score AI responses across multiple dimensions.
Module 5: Test Design for GenAI Systems (6 Hours)
This module focuses on designing test strategies that reflect real-world usage.
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- Writing GenAI-specific test cases
- Scenario-based testing
- Multi-turn conversation testing
- Negative and edge-case testing
- Coverage strategies for AI systems
Learning Focus: Moving from isolated tests to holistic system evaluation.
Module 6: Evaluation Techniques & Metrics (5 Hours)
This module introduces ways to measure and standardize AI evaluation.
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- Human evaluation methods
- Designing scoring rubrics
- Measuring accuracy, relevance, and safety
- Golden datasets
- Trade-offs in evaluation approaches
Learning Focus: Understanding how to quantify quality in a subjective system.
Module 7: Adversarial & Security Testing (5 Hours)
One of the most critical modules, focused on system robustness.
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- Hallucination testing strategies
- Prompt injection attacks
- Jailbreaking techniques
- Guardrail bypass scenarios
- Data leakage risks
Learning Focus: Participants learn how to stress-test AI systems under real-world threats.
Module 8: Industry Playbooks (3 Hours)
This module translates concepts into domain-specific applications.
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- Chatbot testing playbook
- Customer support AI scenarios
- Enterprise AI assistants
- Domain-specific testing considerations
Learning Focus: Reusable approaches for different business contexts.
Module 9: Tools & Practical Workflow (2 Hours)
A lightweight module introducing practical tools and workflows.
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- Prompt testing environments
- Evaluation workflows
- Structuring testing processes
Learning Focus: Making testing repeatable and scalable.
Module 10: Capstone Project – Production Readiness Audit (5 Hours)
This is the most important part of the program.
Scenario: Participants act as AI Reliability Engineers evaluating a GenAI system before launch.
Deliverables:
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- Test strategy document
- Test cases aligned with B.R.A.I.N+
- Evaluation scorecard
- Failure analysis report
- Final recommendation (Go / No-Go decision)
Learning Focus: Applying everything learned in a real-world simulation.
How can I enroll for this course?
OR
For any other details, Call me or Whatsapp me on +91-9133190573
Live Sessions Price:
For LIVE sessions – Offer price after discount is 129 USD 119 109 USD Or USD15000 INR 12900 INR 8900 Rupees.
Sample Course Completion Certificate:
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Note:
To maintain the quality of our training and ensure a smooth learning experience for all participants, we do not allow batch repetition or switching between courses.
To reiterate, moving from one course to another or shifting from one trainer to another (even if it is the same course) is not possible. Changing batches or trainers in any form is strictly not permitted.
We request all learners to attend the scheduled sessions regularly and make the most of their learning journey. Thank you for your understanding and continued support.