This week provides a foundational understanding of machine learning concepts and terminology, focusing on key elements such as common ML models, the roles of features and labels, and the distinctions between training and validation datasets. Learners will also be introduced to deep learning techniques and gain hands-on experience with Automated Machine Learning (AutoML) experiments. By the end of this week, learners will be equipped with the knowledge to identify machine learning tasks, select the appropriate Azure services, and begin developing and training their own ML models with confidence and efficiency.

This week provides a comprehensive understanding of Azure AI Vision and its key capabilities, including image classification, object detection, and optical character recognition (OCR). Learners will explore how these services are applied in real-world scenarios and gain hands-on experience with Azure AI Custom Vision to build and deploy models for specific image tagging and detection tasks. Additionally, the module covers the Azure AI Face service, focusing on facial detection and recognition through practical demonstrations. By the end of this week, learners will be equipped with the knowledge and skills to design and implement intelligent vision solutions using Azure’s powerful AI tools.

This week provides a comprehensive understanding of Natural Language Processing (NLP) and speech technologies using Azure AI services. Learners will explore essential NLP capabilities, such as key phrase extraction, sentiment analysis, language detection, and entity recognition. The module also covers the use of Azure AI Speech for voice recognition and synthesis, enabling the creation of voice-enabled applications. Additionally, learners will delve into Azure’s translation services to implement multilingual solutions that facilitate global communication. By the end of this week , learners will have the skills to design and implement advanced language solutions using Azure AI, including text analysis and custom language model development.

This module provides a comprehensive overview of Generative AI, focusing on its foundational concepts, key features, and real-world applications. Learners will gain insights into responsible AI practices when deploying generative models, ensuring ethical and safe AI development. The module also explores the powerful capabilities of Azure OpenAI services, including code generation, image creation, and natural language processing. Additionally, learners will dive into Azure AI Foundry to explore advanced tools like Retrieval Augmented Generation (RAG) and model optimization strategies, empowering them to enhance AI and ML workflows. By the end of this module, learners will have the practical knowledge required to fine-tune models, optimize performance, and deploy robust AI solutions effectively.