Highlights
Microsoft ML Training:
- Foundational Microsoft ML concepts covered
- Advanced ML techniques explored
- Practical applications and case studies
- Hands-on experience with ML algorithms
- Model optimization strategies
- Impactful decision-making through ML insights
- Azure integration for seamless ML deployment
Unravel Microsoft ML: from foundational concepts to impactful applications, optimize models and make informed decisions.
Course Details
Machine Learning on Azure
- Design a machine learning solution
- Design a data ingestion strategy for machine learning projects
- Design a machine learning model training solution
- Design a model deployment solution
- Design a machine learning operations (MLOps) solution
Explore and configure the Azure Machine Learning workspace
- Explore the Azure Machine Learning workspace resources and assets
- Explore developer tools for workspace interaction
- Make data available in Azure Machine Learning
- Work with compute targets in Azure Machine Learning
- Work with environments in Azure Machine Learning
Experiment with Azure Machine Learning
- Azure Machine Learning Designer
- Find the best classification model with Automated Machine Learning
- Track model training in notebooks with MLflow
Optimize Model Training with Azure Machine Learning
- Run a training script as a command job in Azure Machine Learning
- Track model training with MLflow in jobs
- Perform hyperparameter tuning with Azure Machine Learning
- Run pipelines in Azure Machine Learning
Manage and evaluate models with Azure Machine Learning
- Register an MLflow model in Azure Machine Learning
- Create and explore the Responsible AI dashboard
Deploy and consume models with Azure Machine Learning
- Deploy a model to a managed online endpoint
- Deploy a model to a batch endpoint
Introduction to Microsoft ML
- Foundational concepts in Microsoft Machine Learning
- Understanding ML algorithms and models
- Introduction to Azure ML services
Advanced ML Techniques
- Advanced machine learning techniques and methodologies
- Model optimization strategies
- Feature engineering and selection
Practical Applications and Case Studies
- Real-world applications of Microsoft ML
- Case studies showcasing ML implementations
- Hands-on projects and exercises
Who should attend
This MS ML course is ideal for:
- Data scientists
- Software developers
- AI engineers
- Data analysts
- Business intelligence professionals
- Individuals interested in Microsoft ML technologies
- Professionals seeking to enhance their skills in machine learning and Azure integration
Feedback
4.8 out of 5 average
"Our tailored course provided a well rounded introduction and also covered some intermediate level topics that we needed to know. Clive gave us some best practice ideas and tips to take away. " Brian Leek, Data Analyst, May 2022
“JBI did a great job of customizing their syllabus to suit our business needs and also bringing our team up to speed on the current best practices - very impressive” Brian F, Team Lead, RBS, Data Analysis Course, 20 April 2022