This module introduces the core ideas behind artificial intelligence and explains how AI supports modern digital solutions. Learners build a foundational understanding of machine learning, computer vision, natural language processing, and generative AI in accessible business and technical terms.

Lessons:

• Understand core AI concepts and how artificial intelligence is used in real-world solution design.
• Explore common AI workloads such as prediction, vision, language, and conversational experiences.
• Recognize generative AI basics and how newer AI experiences differ from traditional AI workloads.

Key Topics:

• Artificial intelligence fundamentals
• Common AI workload categories
• Business relevance of AI capabilities
• Introductory generative AI concepts

Labs / Practical Exercises (if applicable):

• Review sample AI solution scenarios and classify them by workload type.
• Identify practical examples of AI use in business or technology contexts.

This module introduces machine learning as a core AI discipline and explains how Azure supports machine learning workflows. Participants learn how models are trained, evaluated, and deployed, while developing a basic understanding of supervised, unsupervised, and responsible model usage.

Lessons:

• Understand machine learning fundamentals and how data is used to train predictive models.
• Explore common machine learning approaches including classification, regression, and clustering.
• Recognize Azure machine learning capabilities used to build and manage intelligent models.

Key Topics:

• Machine learning concepts and model lifecycle
• Training data and prediction scenarios
• Supervised and unsupervised learning
• Azure tools for machine learning solutions

Labs / Practical Exercises (if applicable):

• Review a simple machine learning scenario and identify its model type.
• Explore how a machine learning workflow moves from data to prediction.

This module explains how AI systems can interpret images and visual content. Learners are introduced to Azure computer vision services that support image analysis, optical character recognition, face-related capabilities, and broader visual intelligence scenarios.

Lessons:

• Understand computer vision fundamentals and how image-based AI solutions are used in practice.
• Explore Azure vision capabilities for analyzing images, extracting text, and identifying visual features.
• Recognize business use cases where visual AI improves automation and insight.

Key Topics:

• Image analysis concepts
• Optical character recognition
• Visual feature detection
• Azure services for computer vision

Labs / Practical Exercises (if applicable):

• Review example image analysis outputs and interpret key results.
• Match vision use cases to the appropriate Azure AI capability. 

This module introduces AI capabilities for understanding, generating, and translating human language. Participants learn how Azure services support text analytics, language understanding, translation, speech recognition, and speech synthesis in business and application scenarios.

Lessons:

• Understand natural language processing concepts and how AI works with written text.
• Explore Azure language services for sentiment analysis, entity extraction, translation, and conversational tasks.
• Recognize speech AI capabilities for transcription, synthesis, and multilingual interaction.

Key Topics:

• Natural language processing fundamentals
• Text analytics and language understanding
• Translation and conversational AI
• Speech recognition and text-to-speech

Labs / Practical Exercises (if applicable):

• Review sample text analysis outputs for language-related scenarios.
• Identify where speech services can improve accessibility and user experience. 

This module introduces generative AI and the principles of responsible AI within Azure-based environments. Learners explore how generative models create content, how Azure supports these solutions, and why fairness, transparency, safety, and accountability are essential in AI adoption.

Lessons:

• Understand generative AI fundamentals and how generative models support modern AI applications.
• Explore Azure AI services for generative scenarios and their role in business innovation.
• Recognize responsible AI principles that guide safe and trustworthy AI use.

Key Topics:

• Generative AI concepts and value
• Azure services for generative AI scenarios
• Responsible AI principles
• Safe and trustworthy AI adoption

Labs / Practical Exercises (if applicable):

• Review a generative AI use case and identify potential business value and risks.
• Analyze a basic AI scenario through a responsible AI lens.