AI-900

• Training: get practical technical skills
• Receive a certificate of course attendance
• Small class size: increased instructor interaction
• Authorised test centre: exams taken at our premises
• Expert trainers: imparting real-world experience

Basic functional experience with Azure. Understanding of general AI practices is recommended.

Candidates can achieve this certification by passing the following exam(s).

• Exam AI-900 Microsoft Azure AI Fundamentals

The certification exam can be registered and attempted within 3 months of course/module completion at Logitrain training centre on weekdays during normal business hours (excludes public holidays)

• Identify features of common AI workloads
• Identify guiding principles for responsible AI
• Identify common machine learning types
• Describe core machine learning concepts
• Identify core tasks in creating a machine learning solution
• Describe capabilities of no-code machine learning with Azure Machine Learning:
• Identify common types of computer vision solution:
• Identify Azure tools and services for computer vision tasks
• Identify features of common NLP Workload Scenarios
• Identify Azure tools and services for NLP workloads
• Identify common use cases for conversational AI
• Identify Azure services for conversational AI

This course is likely to add to the employment-related skills of the participants. The skills developed are likely to be used in the course of being an employee or working in a business.

• IT professionals
• AI professionals
• Business intelligence professionals
• Anyone who is interested in learning types of AI solutions and the services on Microsoft Azure

• identify prediction/forecasting workloads
• identify features of anomaly detection workloads
• identify computer vision workloads
• identify natural language processing or knowledge mining workloads
• identify conversational AI workloads
• describe considerations for fairness in an AI solution
• describe considerations for reliability and safety in an AI solution
• describe considerations for privacy and security in an AI solution
• describe considerations for inclusiveness in an AI solution
• describe considerations for transparency in an AI solution
• describe considerations for accountability in an AI solution
• identify regression machine learning scenarios
• identify classification machine learning scenarios
• identify clustering machine learning scenarios
• identify features and labels in a dataset for machine learning
• describe how training and validation datasets are used in machine learning
• describe how machine learning algorithms are used for model training
• select and interpret model evaluation metrics for classification and regression
• describe common features of data ingestion and preparation
• describe common features of feature selection and engineering
• describe common features of model training and evaluation
• describe common features of model deployment and management
• automated Machine Learning tool
• azure Machine Learning designer
• identify features of image classification solutions
• identify features of object detection solutions
• identify features of semantic segmentation solutions
• identify features of optical character recognition solutions
• identify features of facial detection, recognition, and analysis solutions
• identify capabilities of the Computer Vision service
• identify capabilities of the Custom Vision service
• identify capabilities of the Face service
• identify capabilities of the Form Recognizer service
• identify features and uses for key phrase extraction
• identify features and uses for entity recognition
• identify features and uses for sentiment analysis
• identify features and uses for language modeling
• identify features and uses for speech recognition and synthesis
• identify features and uses for translation
• identify capabilities of the Text Analytics service
• identify capabilities of the Language Understanding Intelligence Service (LUIS)
• identify capabilities of the Speech service
• identify capabilities of the Text Translator service
• identify features and uses for webchat bots
• identify features and uses for telephone voice menus
• identify features and uses for personal digital assistants
• identify capabilities of the QnA Maker service
• identify capabilities of the Bot Framework