Microsoft’s AI programs supply complete protection of AI and machine studying ideas for all talent ranges, offering hands-on expertise with instruments like Azure Machine Studying and Dynamics 365 Commerce. They emphasize sensible functions, superior strategies, 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 abilities for excelling within the discipline of synthetic intelligence.
Fundamentals of machine studying
This course gives 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 information or robust math background, specializing in fast studying instruments like scikit-learn, TensorFlow, and PyTorch. It gives simply sufficient familiarity to grasp machine studying examples for merchandise like Azure ML or Azure Databricks.
Implement an information science and machine studying resolution for AI in Microsoft Material
This course covers the information science course of in Microsoft Material, instructing the way to prepare machine studying fashions, preprocess knowledge, and handle fashions with MLflow. It consists of modules on exploring knowledge with notebooks, utilizing Knowledge Wrangler for preprocessing, and producing batch predictions with deployed fashions.
Microsoft Azure AI Fundamentals
This course introduces AI fundamentals and Microsoft Azure providers for AI options, aiming to construct consciousness of AI workloads and related Azure providers. It targets people with fundamental pc and math abilities, overlaying AI workloads, pc imaginative and prescient, pure language processing, doc intelligence, and generative AI by beginner-level modules.
Construct a RAG-based copilot resolution with your individual knowledge utilizing Azure AI Studio
This course covers utilizing Retrieval Augmented Technology (RAG) to boost language fashions with particular knowledge, indexing knowledge with Azure AI Search, and constructing a copilot in Azure AI Studio. It goals to enhance AI-driven ideas and content material technology.
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 investigate buy traits and supply related suggestions. It consists of studying about suggestion lists and parameters.
Fundamentals of Accountable Generative AI
This module teaches the 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 applying of generative AI fashions for NLP in Azure Machine Studying, overlaying subjects corresponding to understanding the Transformer structure and dealing with giant language fashions (LLMs). It consists of modules on fine-tuning LLMs for particular duties and using immediate stream to develop functions 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 improvement and software ideas corresponding to equity, reliability, privateness, inclusiveness, transparency, and accountability. It consists of modules on understanding and making use of these ideas, particularly in studying environments, with interactive workout routines for sensible implementation.
