Training: Azure Machine Learning
Level
IntermediateDuration
16h / 2 daysDate
Individually arrangedPrice
Individually arrangedTraining: Azure Machine Learning
The Azure Machine Learning training is an intensive two-day course focused on the practical application of tools and services available in Azure for building, training, and deploying machine learning models. The program is designed so that 80% of the time is dedicated to hands-on workshops and 20% to theory. Participants will learn how to fully leverage the Azure Machine Learning platform, working with real-world examples and use cases.
What will you learn?
- How to configure and manage the Azure ML Workspace
- How to deploy ML models on Azure ML Service and monitor their performance
- How to perform exploratory data analysis (EDA) and train ML models using Azure ML Designer and AutoML
- How to integrate ML models with other Azure services, such as Databricks and Cognitive Services
Prerequisites
- Basic knowledge of Python programming
- Experience with cloud services is an advantage
- Basic understanding of machine learning
Who is this training for?
Developers and data engineers who want to expand their skills in machine learning on Azure-
IT specialists who want to use Azure Machine Learning to automate data processing and prediction
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Data scientists and analysts aiming to train and deploy ML models in a production environment
Training Program
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Day 1: Introduction to Azure Machine Learning and Basics
- Fundamentals of Azure Machine Learning
- Overview of the Azure ecosystem and its ML services
- Configuring the Azure ML Workspace
- Preparing data and performing exploratory data analysis (EDA)
- Importing and processing data in Azure
- Conducting EDA with Azure tools
- Training models in Azure
- Introduction to Azure ML Designer
- Automating model training with Azure AutoML
- Training your first model
- Hands-on exercises with real-world datasets
- Analyzing results and evaluating model performance
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Day 2: Advanced Techniques and Practical Applications
- Advanced model training techniques
- Using custom scripts for model training
- Leveraging GPUs and compute clusters to speed up training
- Deploying and monitoring models
- Deploying ML models on Azure ML Service
- Monitoring and managing deployed models
- Model deployment and optimization
- Hands-on exercises in model deployment
- Model optimization and hyperparameter tuning
