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Generative AI in Software Testing (Functional & Automation Testing)-Day 2

Generative AI in Software Testing – Functional & Automation Testing – Live Training (Types of language models, prompt engineering, prompting techniques, leveraging AI in different phases)   Isha Training Solutions presents an Extensive and Highly Interactive Course: “Generative AI in …

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Event Information

  • Price Rs.6,900.00 per participant
  • Location Online
  • Start Time 8:30 pm March 13, 2025
  • Finish Time 9:30 pm March 13, 2025
  • Capacity Limited to 100 people

Generative AI in Software Testing – Functional & Automation Testing – Live Training

(Types of language models, prompt engineering, prompting techniques, leveraging AI in different phases)

 

Isha Training Solutions presents an Extensive and Highly Interactive Course: “Generative AI in Software Testing: Functional & Automation Testing” Led by a seasoned industry expert with over 12 years of hands-on experience, this course offers comprehensive, practical insights into Generative AI applications in software testing. With a curriculum designed to align with current job market trends and industry demands, participants will gain in-depth knowledge of Generative AI concepts through real-world examples and hands-on practice.

 

The use of Generative AI is becoming increasinlgy important in every phase of SDLC. It can also be leveraged in the field of software testing. To harness the potential of this technology in testing, you must learn to interact with different Gen AI tools. This course is designed to make you skilled to use LLMs in different phases of software testing.

 

About the Instructor:

Chandra Kumar has over 12 years of experience in Performance Engineering and Testing. He is a BlazeMeter Certified Apache JMeter and Microfocus LoadRunner Certified Professional. Chandra has extensive expertise with performance testing tools such as Apache JMeter, LoadRunner, and Neoload, as well as APM tools including Dynatrace, AppDynamics, PerfMon, and NMON.He has been providing professional training on Performance Test Tools and Performance Engineering for more than 2 years. In addition, he brings his expertise to “Generative AI in Software Testing: Functional, Automation, and Performance Testing”, offering participants practical insights and hands-on experience in leveraging Generative AI for enhanced software testing.

 

Sample Videos:

“Generative AI in Software Testing (Functional & Automation Testing)”-Demo session Video

“Generative AI in Software Testing (Functional & Automation Testing)”-Day 1 March session Video

Live Sessions  Price:

For LIVE sessions – Offer price after discount is 300 USD 259 USD 99 USD Or 13000 INR 12900 INR 6900 Rupees

Enroll For Free Demo

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Free Day 2 Session:

13th March @ 8:30 PM – 9:30 PM (IST) (Indian Timings)

13th March @ 11:00 AM – 12:00 PM (EST) (U.S Timings)

13th March @ 3:00 PM – 4:00 PM (BST) (UK Timings)

 

Class Schedule:

For Participants in India: Monday to Friday @ 8:30 PM – 9:30 PM (IST)

For Participants in the US: Sunday to Thursday @ 11:00 AM – 12:00 PM (EST)

For Participants in the UK: Monday to Friday @ 3:00 PM – 4:00 PM (BST)

 

What students have to say about Chandra Kumar:

“The Generative AI course was a game-changer! Chandra Sir’s practical examples, along with his deep knowledge, made learning enjoyable. The focus on performance testing with AI tools was particularly enlightening. Thank you for an amazing training experience!”- Arjun Verma

“A transformative learning experience! Chandra Sir’s expertise in Generative AI for software testing opened up new horizons for me. His teaching, combined with hands-on projects, was highly effective. I highly recommend this course to anyone interested in modernizing their testing approach.” – Sneha Reddy

“Excellent session! The detailed coverage of functional, automation, and performance testing using AI tools was exactly what I needed. Chandra Sir’s clear explanations and practical demos provided great insights. I appreciate the real-world case studies and tips shared during the sessions.”- Amit Raj

“Chandra Sir’s teaching style is outstanding! He made advanced AI-driven testing techniques feel simple and accessible. The hands-on exercises were well-structured, and I loved how he answered every question patiently. This training has given me the confidence to explore automation testing with Generative AI.” – Neha Gupta

“The training was insightful and engaging! Chandra Sir explained Generative AI concepts in software testing with real-world examples, making it easy to understand complex topics. His step-by-step approach to automation and performance testing techniques using AI was impressive. Looking forward to applying these skills in my projects!”- Rahul Sharma

 

What will I learn by the end of this course?

  • Master Prompting Techniques: Gain the skills to efficiently generate test cases and test scripts using AI-driven methods.
  • Automate Test Artifact Creation: Learn how to instantly generate key test artifacts such as Test Plans, Test Cases, Test Data, and Bug Templates based on given business requirements.
  • Explore AI-Powered Testing Tools: Get an overview of the latest AI-powered testing tools in the market and understand their capabilities in enhancing the software testing process.

 

Salient Features

  • 20 Hours of On-Demand Live Sessions and Recorded Videos: Gain lifetime access to extensive training materials.
  • Course Completion Certificate: Receive a certificate upon successful completion of the course.
  • Hands-On Projects: Engage in real-world projects and live applications to apply the skills learned, ensuring practical, hands-on experience

 

Who can enroll for this course?

  • Software Testing Professionals: Ideal for QA engineers, test analysts, and automation testers seeking to enhance their skills with AI-driven testing techniques.
  • Generative AI Enthusiasts: Perfect for individuals interested in exploring the application of AI in software testing and automation.

 

Course syllabus:

Gen AI Fundamentals – (3 Hours)

Introduction, Key concepts and terms:

  • Overview of Artificial Intelligence (AI) and its significance
  • Machine learning
  • Deep learning
  • Natural language processing
  • Generative AI
  • Language model

Types of language models:

  • Large language models
  • Small language models

How do LLMs work and their limitations

  • Architecture and mechanisms behind LLMs
  • Limitations: Bias, hallucinations, and computational cost

What is a prompt:

  • Definition and role of prompts in AI interactions

Language model parameters

  • Explanation of parameters like tokens, context length, and temperature
  • Impact of parameter tuning on responses

Security risks

  • Data privacy concerns
  • Risks of adversarial attacks and misinformation generation

Applications and use cases of AI

  • Chatbots, virtual assistants, and customer service
  • Code generation, content creation, and predictive analytics

 

Prompt Engineering – (4 Hours)

What is prompt engineering

  • Introduction to prompt engineering
  • Definition and significance of crafting effective prompts

Prompt components

  • Basic prompt structure
  • Prompt frameworks

Formatting and prompt parameters

  • Formatting styles
  • Temperature, Max tokens and Stop sequences

Prompt tuning process

  • Adjusting prompts for specific responses
  • Iterative testing and refinement of prompt phrasing

Different prompting techniques

  • Shot based prompting
  • Sequential prompting
  • Context guiding prompting

Best practices

  • Best practices in prompt engineering

 

AI in Software Testing – (11 Hours)

Requirement analysis

  • Requirement analysis with AI conversational tools
  • Deeper understanding of requirements
  • Identify testable requirements
  • Requirement traceability matrix

Test planning

  • Test strategy and approach preparation
  • Test plan preparation
  • Selection of different testing tools
  • Effort estimation
  • Risk-based test prioritization

Test case development

  • Functional test case creation
  • Automation script development
  • Optimizing test coverage and identifying edge cases
  • Test data creation

Test environment set up

  • Test environment creation plan
  • Test environment selection
  • Verification of test environment

Test execution

  • Defect creation
  • Defect reporting
  • Daily and weekly status

Test cycle closure

  • Assess the test closure cycle
  • Test metrics preparation
  • Test report creation