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AI for Testers

This hands-on course helps testers understand how to verify Artificial Intelligence (AI)-based systems and use AI during testing and software quality assurance activities.

Full Description and Outline

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Dates
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Price
Jan 21—Jan 23, 2025
Live Virtual
Virtual Classroom
Virtual Classroom
$1,495
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Feb 11—Feb 13, 2025
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Mar 18—Mar 20, 2025
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Apr 22—Apr 23, 2025
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May 27—May 29, 2025
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Virtual Classroom
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Jun 24—Jun 26, 2025
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Mar 26—Mar 27, 2025
Public Classroom
Microsoft Innovation Hub, Arlington, VA
Microsoft Innovation Hub, Arlington, VA at AI Training Week DC
$1,545
ATTEND
Select a learning mode button (Public, Live Virtual, etc.) for pricing, details, and a downloadable fact sheet.
Ways to Save

2025 Supercharge Learning Subscription - Unlimited Training

Are you ready to supercharge your software career and become a master in your field? Our 2025 Supercharge Learning Subscription is designed to empower you with a comprehensive set of skills, setting the stage for success in the first half of 2025.

Get unlimited access to your choice of live virtual training courses delivered between January 1, 2025 and June 30, 2025 all for a one-time fee of $5,000. That’s a potential savings of over $20,000!

The deadline to register is January 31, 2025.

Learn More and Register Here.

 

Description

Artificial Intelligence (AI) has taken the world by storm, increasing the productivity of workers in a wide range of industries, especially software. But, it’s also understandably led to uncertainty and fear about the personal and implications for disciplines such as software testing.

If you’re interested in cutting through the hype and understanding how AI affects the testing profession, then this course is for you. In this hands-on class, you will learn how to test systems with AI components and how to apply AI to the process of testing itself.

Key takeaways from this class include:

  • Learn how to effectively test and validate AI model input data and datasets.
  • Understand how to effectively test AI models during model development and training.
  • Apply effective testing techniques to software systems that include AI models.
  • Learning how to leverage AI to support test case and script generation.
  • Understand how to leverage AI to support test planning and management.

Who Should Attend
This course is ideal for those who test AI-based systems or wish to use AI to support their current software testing activities. This includes those in hands-on testing roles or test managers, as well as software developers and development managers.

Laptop and RDP Required
This class involves hands-on activities using sample software to better facilitate learning. Each student should bring a laptop with a remote desktop protocol (RDP) client pre-installed. Connection specifics and credentials will be supplied during class. Please work with your IT Admin before class to verify that your RDP client can be used to access a virtual machine running in the Amazon Web Services (AWS) environment. If you or your Admin have questions about the specific applications involved, contact our Client Support team.

Questions? 929.777.8102 [email protected]
Course Outline

Session 1: Introduction to AI/ML and AI for Testers

  • Definition of AI and AI effect
  • AI-based and conventional systems
  • Types of AI
  • Introduction to machine learning and neural networks
  • Generative AI and LLMs
  • Introduction to AI for Testing
  • Example AI-based system

Session 2: Testing AI Models and their Data

  • Machine learning process
  • Testing input data
  • Testing AI model data pipelines
  • Testing AI models
  • Testing AI model training pipelines
  • Demos and Hands-on Exercises

Session 3: Testing AI-based Systems

  • End-to-end AI-based system process
  • Model testing and delivery options
  • AI-based systems testing process
  • Component integration testing
  • System testing
  • Acceptance testing
  • Model monitoring
  • Model retraining
  • Demos and Hands-on Exercises

Session 4: AI-Assisted Test Planning and Management

  • AI-based testing process
  • Prompt engineering for testers
  • AI in test planning & documentation
  • AI for defect management
  • Using AI to generate and transform test data
  • Demos and Hands-on Exercises

Session 5: AI-Assisted Testing

  • How AI helps testing
  • AI capabilities that support test automation
  • AI-based test script generation
  • AI-assisted UI testing
  • Using AI to optimize regression test suites
  • Demos and Hands-on Exercises

Session 6: Wrapup

  • Aha moments
  • References
  • Course survey
  • Next steps and additional information
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✓ = Guaranteed to Run
Dates
Mode
Location
Price
Mar 26—Mar 27, 2025
Public Classroom
Microsoft Innovation Hub, Arlington, VA
Microsoft Innovation Hub, Arlington, VA at AI Training Week DC
$1,545
ATTEND
Download Fact Sheet
Price: $1,545 USD
Course Duration: 2 Days
Description

Artificial Intelligence (AI) has taken the world by storm, increasing the productivity of workers in a wide range of industries, especially software. But, it’s also understandably led to uncertainty and fear about the personal and implications for disciplines such as software testing.

If you’re interested in cutting through the hype and understanding how AI affects the testing profession, then this course is for you. In this hands-on class, you will learn how to test systems with AI components and how to apply AI to the process of testing itself.

Key takeaways from this class include:

  • Learn how to effectively test and validate AI model input data and datasets.
  • Understand how to effectively test AI models during model development and training.
  • Apply effective testing techniques to software systems that include AI models.
  • Learning how to leverage AI to support test case and script generation.
  • Understand how to leverage AI to support test planning and management.

Who Should Attend
This course is ideal for those who test AI-based systems or wish to use AI to support their current software testing activities. This includes those in hands-on testing roles or test managers, as well as software developers and development managers.

Laptop and RDP Required
This class involves hands-on activities using sample software to better facilitate learning. Each student should bring a laptop with a remote desktop protocol (RDP) client pre-installed. Connection specifics and credentials will be supplied during class. Please work with your IT Admin before class to verify that your RDP client can be used to access a virtual machine running in the Amazon Web Services (AWS) environment. If you or your Admin have questions about the specific applications involved, contact our Client Support team.

Questions? 929.777.8102 [email protected]
Course Outline

Session 1: Introduction to AI/ML and AI for Testers

  • Definition of AI and AI effect
  • AI-based and conventional systems
  • Types of AI
  • Introduction to machine learning and neural networks
  • Generative AI and LLMs
  • Introduction to AI for Testing
  • Example AI-based system

Session 2: Testing AI Models and their Data

  • Machine learning process
  • Testing input data
  • Testing AI model data pipelines
  • Testing AI models
  • Testing AI model training pipelines
  • Demos and Hands-on Exercises

Session 3: Testing AI-based Systems

  • End-to-end AI-based system process
  • Model testing and delivery options
  • AI-based systems testing process
  • Component integration testing
  • System testing
  • Acceptance testing
  • Model monitoring
  • Model retraining
  • Demos and Hands-on Exercises

Session 4: AI-Assisted Test Planning and Management

  • AI-based testing process
  • Prompt engineering for testers
  • AI in test planning & documentation
  • AI for defect management
  • Using AI to generate and transform test data
  • Demos and Hands-on Exercises

Session 5: AI-Assisted Testing

  • How AI helps testing
  • AI capabilities that support test automation
  • AI-based test script generation
  • AI-assisted UI testing
  • Using AI to optimize regression test suites
  • Demos and Hands-on Exercises

Session 6: Wrapup

  • Aha moments
  • References
  • Course survey
  • Next steps and additional information

Class Schedule

Sign-In/Registration 7:30 - 8:30 a.m.
Morning Session 8:30 a.m. - 12:00 p.m.
Lunch 12:00 - 1:00 p.m.
Afternoon Session 1:00 - 5:00 p.m.
Times represent the typical daily schedule. Please confirm your schedule at registration.

Class Fee Includes

• Digital course materials
• Continental breakfasts and refreshment breaks
• Lunches

Instructors
Jeff Pierce

Jeff Pierce

Jeff Pierce has more than 20 years of experience in software engineering management, specializing in program, project, and software quality assurance management. Jeff is also experienced in building technical teams that are rapidly able to implement solutions and deliver business value. More recently, Jeff has focused on Agile project management...Learn More

Jonathan Kauffman

Jonathan Miller Kauffman

Jonathan Miller Kauffman works as an agile software development and test consultant at Coveros. In this role, Jonathan has helped both government and commercial organizations develop and test high-quality applications, and he has gained his experience by working with healthcare, biomedical device, and research organizations. Jonathan also presents at and...Learn More

Tom-Stiehm

Tom Stiehm

Tom Stiehm is a 20 year veteran of the Information Technology industry. He has spent the past 10 years managing, designing and implementing software products and applications using agile software development methods. Prior to Coveros, Tom held a variety of CTO and architect positions at software development companies. Tom is...Learn More

✓ = Guaranteed to Run
Dates
Mode
Location
Price
Jan 21—Jan 23, 2025
Live Virtual
Virtual Classroom
Virtual Classroom
$1,495
Attend
Feb 11—Feb 13, 2025
Live Virtual
Virtual Classroom
Virtual Classroom
$1,495
Attend
Mar 18—Mar 20, 2025
Live Virtual
Virtual Classroom
Virtual Classroom
$1,495
Attend
Apr 22—Apr 23, 2025
Live Virtual
Virtual Classroom
Virtual Classroom
$1,495
Attend
May 27—May 29, 2025
Live Virtual
Virtual Classroom
Virtual Classroom
$1,495
Attend
Jun 24—Jun 26, 2025
Live Virtual
Virtual Classroom
Virtual Classroom
$1,495
Attend
Download Fact Sheet
Price: $1,495 USD
Course Duration: 3 Days
Ways to Save

2025 Supercharge Learning Subscription - Unlimited Training

Are you ready to supercharge your software career and become a master in your field? Our 2025 Supercharge Learning Subscription is designed to empower you with a comprehensive set of skills, setting the stage for success in the first half of 2025.

Get unlimited access to your choice of live virtual training courses delivered between January 1, 2025 and June 30, 2025 all for a one-time fee of $5,000. That’s a potential savings of over $20,000!

The deadline to register is January 31, 2025.

Learn More and Register Here.

 

Description

Artificial Intelligence (AI) has taken the world by storm, increasing the productivity of workers in a wide range of industries, especially software. But, it’s also understandably led to uncertainty and fear about the personal and implications for disciplines such as software testing.

If you’re interested in cutting through the hype and understanding how AI affects the testing profession, then this course is for you. In this hands-on class, you will learn how to test systems with AI components and how to apply AI to the process of testing itself.

Key takeaways from this class include:

  • Learn how to effectively test and validate AI model input data and datasets.
  • Understand how to effectively test AI models during model development and training.
  • Apply effective testing techniques to software systems that include AI models.
  • Learning how to leverage AI to support test case and script generation.
  • Understand how to leverage AI to support test planning and management.

Who Should Attend
This course is ideal for those who test AI-based systems or wish to use AI to support their current software testing activities. This includes those in hands-on testing roles or test managers, as well as software developers and development managers.

Laptop and RDP Required
This class involves hands-on activities using sample software to better facilitate learning. Each student should bring a laptop with a remote desktop protocol (RDP) client pre-installed. Connection specifics and credentials will be supplied during class. Please work with your IT Admin before class to verify that your RDP client can be used to access a virtual machine running in the Amazon Web Services (AWS) environment. If you or your Admin have questions about the specific applications involved, contact our Client Support team.

Questions? 929.777.8102 [email protected]
Course Outline

Session 1: Introduction to AI/ML and AI for Testers

  • Definition of AI and AI effect
  • AI-based and conventional systems
  • Types of AI
  • Introduction to machine learning and neural networks
  • Generative AI and LLMs
  • Introduction to AI for Testing
  • Example AI-based system

Session 2: Testing AI Models and their Data

  • Machine learning process
  • Testing input data
  • Testing AI model data pipelines
  • Testing AI models
  • Testing AI model training pipelines
  • Demos and Hands-on Exercises

Session 3: Testing AI-based Systems

  • End-to-end AI-based system process
  • Model testing and delivery options
  • AI-based systems testing process
  • Component integration testing
  • System testing
  • Acceptance testing
  • Model monitoring
  • Model retraining
  • Demos and Hands-on Exercises

Session 4: AI-Assisted Test Planning and Management

  • AI-based testing process
  • Prompt engineering for testers
  • AI in test planning & documentation
  • AI for defect management
  • Using AI to generate and transform test data
  • Demos and Hands-on Exercises

Session 5: AI-Assisted Testing

  • How AI helps testing
  • AI capabilities that support test automation
  • AI-based test script generation
  • AI-assisted UI testing
  • Using AI to optimize regression test suites
  • Demos and Hands-on Exercises

Session 6: Wrapup

  • Aha moments
  • References
  • Course survey
  • Next steps and additional information

Class Fee Includes
  • Easy course access: Attend training right from your computer and easily connect your audio via computer or phone. Easy and quick access fits today’s working style and eliminates expensive travel and long days in the classroom.
  • Live, expert instruction: Instructors are sought-after practitioners, highly-experienced in the industry who deliver a professional learning experience in real-time. 
  • Valuable course materials: Courses cover the same professional content as our classroom training, and students have direct access to valuable materials. 
  • Rich virtual learning environment: A variety of tools are built in to the learning platform to engage learners through dynamic delivery and to facilitate a multi-directional flow of information.
  • Hands-on exercises: An essential component to any learning experience is applying what you have learned. Using the latest technology, your instructor can provide hands-on exercises, group activities, and breakout sessions. 
  • Real-time communication: Communicate real-time directly with the instructor. Ask questions, provide comments, and participate in the class discussions.
  • Peer interaction: Networking with peers has always been a valuable part of any classroom training. Live Virtual training gives you the opportunity to interact with and learn from the other attendees during breakout sessions, course lecture, and Q&A.
  • Small class size: Live Virtual courses are limited in small class size to ensure an opportunity for personal interaction.

Bring this course to your team at your site. Contact us to learn more at 929.777.8102.

Don't see a date that fits your schedule? Contact us for scheduling options at 929.777.8102
Download Fact Sheet
Course Duration: 3 Days
Description

Artificial Intelligence (AI) has taken the world by storm, increasing the productivity of workers in a wide range of industries, especially software. But, it’s also understandably led to uncertainty and fear about the personal and implications for disciplines such as software testing.

If you’re interested in cutting through the hype and understanding how AI affects the testing profession, then this course is for you. In this hands-on class, you will learn how to test systems with AI components and how to apply AI to the process of testing itself.

Key takeaways from this class include:

  • Learn how to effectively test and validate AI model input data and datasets.
  • Understand how to effectively test AI models during model development and training.
  • Apply effective testing techniques to software systems that include AI models.
  • Learning how to leverage AI to support test case and script generation.
  • Understand how to leverage AI to support test planning and management.

Who Should Attend
This course is ideal for those who test AI-based systems or wish to use AI to support their current software testing activities. This includes those in hands-on testing roles or test managers, as well as software developers and development managers.

Laptop and RDP Required
This class involves hands-on activities using sample software to better facilitate learning. Each student should bring a laptop with a remote desktop protocol (RDP) client pre-installed. Connection specifics and credentials will be supplied during class. Please work with your IT Admin before class to verify that your RDP client can be used to access a virtual machine running in the Amazon Web Services (AWS) environment. If you or your Admin have questions about the specific applications involved, contact our Client Support team.

Questions? 929.777.8102 [email protected]
Course Outline

Session 1: Introduction to AI/ML and AI for Testers

  • Definition of AI and AI effect
  • AI-based and conventional systems
  • Types of AI
  • Introduction to machine learning and neural networks
  • Generative AI and LLMs
  • Introduction to AI for Testing
  • Example AI-based system

Session 2: Testing AI Models and their Data

  • Machine learning process
  • Testing input data
  • Testing AI model data pipelines
  • Testing AI models
  • Testing AI model training pipelines
  • Demos and Hands-on Exercises

Session 3: Testing AI-based Systems

  • End-to-end AI-based system process
  • Model testing and delivery options
  • AI-based systems testing process
  • Component integration testing
  • System testing
  • Acceptance testing
  • Model monitoring
  • Model retraining
  • Demos and Hands-on Exercises

Session 4: AI-Assisted Test Planning and Management

  • AI-based testing process
  • Prompt engineering for testers
  • AI in test planning & documentation
  • AI for defect management
  • Using AI to generate and transform test data
  • Demos and Hands-on Exercises

Session 5: AI-Assisted Testing

  • How AI helps testing
  • AI capabilities that support test automation
  • AI-based test script generation
  • AI-assisted UI testing
  • Using AI to optimize regression test suites
  • Demos and Hands-on Exercises

Session 6: Wrapup

  • Aha moments
  • References
  • Course survey
  • Next steps and additional information

Questions?

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