Certified Tester in Artificial Intelligence Online Training Outside India

Artificial Intelligence in Testing

With the current trends in technology and the growing incorporation of Artificial Intelligence and Machine Learning, Artificial Intelligence United (AiU) was created to support the understanding of the implementation of these important advancements. AiU - Certified Tester in Artificial Intelligence (AiU-CTAI) is a 3-day practical certification course, which goes beyond the fundamentals of Artificial Intelligence and Machine Learning, to discover the differences associated with testing in this new world. Join the Artificial Intelligence United community and embark on your AI/ML journey today. 

Target Audience

Anybody who has to test or manage the testing of systems that involve AI. 

Pre-requisites  

In general, there are no prerequisites for attending an AiU course or taking the exam. We do recommend you hold the ISTQB CTFL certificate and have first hand experience in the field of AI & ML. 

Course Outline

1. Introduction to Artificial Intelligence  

• Definition of Artificial Intelligence (AI)  
• Types of AI  
• Definition of ML  
• Supervised Learning - Classification and Regression  
• Unsupervised Learning – Clustering and Association  
• Reinforcement Learning  
• Deep Learning and the Types of Neural Networks  
• Stages of the ML Process – CRISP-DM Process  
• Steps for the Identification of the ML Problem Type  

2. - Overview of Testing AI Systems  

• Offline and Online Testing of AI Systems  
• Testing of AI systems vs Traditional (non-AI) Systems  
• AI Quality Characteristics  

3. Offline Testing of AI Systems  

• Steps of Data Preparation and Pre-processing  
• Processing of Unstructured Data (Images)  
• Processing of Unstructured Data (Text)  
• Data Imputation, Data Visualization  
• Anomaly/Outliers Detection and Techniques  
• Dimensionality Reduction  
• Role of Metrics  
• Inertia and Adjusted Rand Score  
• Support, Confidence and Lift metrics  
• Confusion Matrix, Accuracy, Precision, Recall, Specificity and F1-Score  
• RMSE and R-Square  
• Training, Validation and Testing Datasets  
• Underfitting and Overfitting and Cross-validation methods  
• Types of Analytics 

4. Online Testing of AI Systems

• Components of an Intelligent Application and their Testing Needs  
• Interaction of AI and Non-AI Parts  
• Linguistic Analysis-Based Test Design  
• Test a Chatbot  

5. Explainable AI  

• Explainable AI and its Need  
• LIME  
• CAM for Neural Networks  

6. Risks and Test Strategy for AI Systems  

• Risks of Testing AI Systems  
• Risk of Using Pre-Trained Models  
• Risk of Concept Drift (CD)  
• Challenges of AI Test Environment  
• Test Strategy for Testing AI Applications  

7. AI in Testing  

• AI for Software Testing Life Cycle (STLC)  
• AI for Reporting and Smart Dashboards  
• AI based automation tools 

Artificial Intelligence in Testing Certification Exam:

40 multiple-choice questions to be completed in 60 minutes  

65% required to pass (26/40)  

Exam mode - Paper & Pen 

About Verity Software

At Verity Software, we provide our customers with comprehensive customer training programs to ensure clients can derive maximum benefit from our solutions as quickly and easily as possible. Training programs can be tailored to meet the needs of all types of users including the project team, super users and regular users.

Our delivery team consists of leading innovators and very senior technical consultants, each having over a decade of design and development experience. We are the trusted partners by organizations for all their technical training needs. Our training ratings are always 4.5 Out of 5 by the delegates and training managers.  

Verity offers certification course across the spectrum of Software Testing courses from globally recognized accredited partners like ISTQB, ITB, SALT, iSQI and Experiments that help your team to:  

• Increase credibility and professionalism for the team & individual.  
• Get recognized globally.
• Build consistency across delivery, best practices, and vocabulary.
• Prove that their learning is backed by the ability to perform