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Real-world, hands-on demonstrations using Azure ML Studio
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Advanced Azure tools such as AutoML, Model Management, and MLOps
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Scalable machine learning pipelines for efficient, reproducible workflows
This course empowers professionals to master Azure Machine Learning, a leading tool for developing and deploying ML models. Starting with key machine learning concepts, you’ll dive into supervised, unsupervised, and reinforcement learning, applying them through Azure ML Studio. Hands-on labs will guide you through setting up experiments, preprocessing data, and selecting the best models for your tasks.
You’ll also explore advanced topics like model evaluation, optimization, and deployment using Azure’s cloud resources, ensuring efficient and scalable workflows. With Azure’s flexible ecosystem, you’ll manage data, automate tasks with AutoML, and address challenges like overfitting and model drift.
The course covers real-world applications in industries like healthcare and finance, while also introducing Generative AI tools like GPT and DALL·E. Ethical AI practices are emphasized, preparing you to build responsible, scalable AI systems. This course equips you with the skills to deploy, monitor, and improve ML models in any industry.
This course is aimed at data scientists, machine learning engineers, and professionals with a technical background who wish to leverage Azure’s machine learning capabilities. Prerequisites include basic knowledge of programming (preferably Python) and familiarity with machine learning concepts.
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Comprehensive machine learning techniques with Azure ML Studio
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Hands-on demonstrations for real-world machine learning applications
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Advanced tools like AutoML, Model Management, and MLOps
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Scalable machine learning pipelines for efficient workflows
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Real-world industry applications in healthcare and finance
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Generative AI with GPT and DALL·E in Azure ML Studio