Prime Synthetic Intelligence AI Programs by Microsoft

Microsoft’s AI programs supply complete protection of AI and machine studying ideas for all ability ranges, offering hands-on expertise with instruments like Azure Machine Studying and Dynamics 365 Commerce. They emphasize sensible purposes, superior methods, and accountable AI practices, equipping learners to develop and deploy AI options ethically and successfully. This text lists the highest Microsoft AI programs that present important expertise for excelling within the discipline of synthetic intelligence.

Fundamentals of machine studying

This course supplies a foundational understanding of machine studying, together with its core ideas, sorts, and concerns for coaching and evaluating fashions. It additionally covers deep studying fundamentals and using automated machine studying in Azure Machine Studying service.

Create machine studying fashions

This course is good for these with some machine studying data or robust math background, specializing in fast studying instruments like scikit-learn, TensorFlow, and PyTorch. It supplies simply sufficient familiarity to grasp machine studying examples for merchandise like Azure ML or Azure Databricks.

Implement a knowledge science and machine studying answer for AI in Microsoft Cloth

This course covers the information science course of in Microsoft Cloth, instructing the best way to practice machine studying fashions, preprocess information, and handle fashions with MLflow. It contains modules on exploring information with notebooks, utilizing Information Wrangler for preprocessing, and producing batch predictions with deployed fashions.

Microsoft Azure AI Fundamentals

This course introduces AI fundamentals and Microsoft Azure companies for AI options, aiming to construct consciousness of AI workloads and related Azure companies. It targets people with fundamental pc and math expertise, protecting AI workloads, pc imaginative and prescient, pure language processing, doc intelligence, and generative AI via beginner-level modules.

Construct a RAG-based copilot answer with your individual information utilizing Azure AI Studio

This course covers utilizing Retrieval Augmented Technology (RAG) to boost language fashions with particular information, indexing information with Azure AI Search, and constructing a copilot in Azure AI Studio. It goals to enhance AI-driven options and content material era.

Work with product suggestions in Dynamics 365 Commerce

This module covers enabling and dealing with product suggestions in Dynamics 365 Commerce, which use AI and machine studying to research buy tendencies and supply related suggestions. It contains studying about suggestion lists and parameters.

Fundamentals of Accountable Generative AI

This module teaches the best way to develop generative AI options responsibly by describing a course of for minimizing dangerous content material. It covers figuring out, measuring, and mitigating potential harms, and getting ready for accountable deployment and operation of generative AI options.

Apply immediate engineering with Azure OpenAI Service

This course teaches immediate engineering in Azure OpenAI, specializing in designing and optimizing prompts to boost mannequin efficiency. It covers creating clear directions, requesting particular output compositions, and utilizing contextual content material to enhance response accuracy and relevancy.

Work with generative synthetic intelligence (AI) fashions in Azure Machine Studying

This course explores the appliance of generative AI fashions for NLP in Azure Machine Studying, protecting subjects akin to understanding the Transformer structure and dealing with giant language fashions (LLMs). It contains modules on fine-tuning LLMs for particular duties and using immediate movement to develop purposes leveraging LLMs, with conditions of familiarity with Azure and the Azure portal.

Accountable use of synthetic intelligence in training

This course explores Microsoft’s Accountable AI framework, emphasizing moral AI growth and utility rules akin to equity, reliability, privateness, inclusiveness, transparency, and accountability. It contains modules on understanding and making use of these rules, particularly in studying environments, with interactive workout routines for sensible implementation.