AI-102 Designing & Implementing an Azure AI Solution

Upcoming Schedules:

•    2nd September 2024 - Monday
•    14th October 2024 - Monday
•    18th November 2024 - Monday
•    9th December 2024 - Monday

Course Overview:

The "Designing & Implementing an Azure AI Solution" course is designed to equip participants with the knowledge and skills required to design and implement AI solutions using Microsoft Azure services. The course covers a range of AI services and tools available on Azure, focusing on their integration to build intelligent applications.

Target Audience:

This course is suitable for AI engineers, data scientists, developers, and IT professionals who want to leverage Azure AI services to design and deploy intelligent solutions.

Prerequisites:

Participants should have a fundamental understanding of Azure services, machine learning concepts, programming skills (preferably Python), and familiarity with data handling and analysis.

What's Included :

• 4 day instructor-led training
• Official Study guide
• Labs (as required) for hands-on learning
• Certified Trainer delivering the class
• Case studies of implementations
• Hands-on projects & exercises to apply concepts learned throughout the course
• Q&A sessions and troubleshooting exercises

Module 1: Introduction to Azure AI Solutions

• Overview of Azure AI services and capabilities
• Understanding the Azure AI stack and ecosystem
• Ethical considerations and responsible AI practices

Module 2: Designing AI Solutions on Azure

• Identifying AI scenarios and use cases
• Architectural considerations for AI solutions
• Designing scalable and reliable AI architectures on Azure

Module 3: Implementing Cognitive Services

• Introduction to Azure Cognitive Services
• Implementing computer vision solutions
• Building natural language processing (NLP) applications
• Developing conversational AI with Azure Bot Services

Module 4: Building Machine Learning Models with Azure ML

• Introduction to Azure Machine Learning
• Data preparation and feature engineering
• Training and evaluating machine learning models
• Hyperparameter tuning and model optimization

Module 5: Implementing AI Solutions with Azure Databricks

• Overview of Azure Databricks for big data and AI
• Integrating Azure Databricks with Azure AI services
• Building end-to-end AI pipelines with Databricks and Azure ML

Module 6: Implementing AI Solutions with Azure Cognitive Search

• Introduction to Azure Cognitive Search
• Building search-based AI solutions
• Integrating Cognitive Search with AI models and data sources

Module 7: Deploying and Managing AI Solutions

• Deploying AI models as web services with Azure ML
• Monitoring and managing AI solutions in production
• Scaling AI solutions with Azure Kubernetes Service (AKS)

Module 8: Securing and Optimizing AI Solutions

• Implementing security best practices for AI solutions
• Optimizing AI models for performance and cost-efficiency
• Continuous improvement and model retraining strategies

This course outline provides a structured approach to learning about Azure AI solutions, from understanding the fundamentals to designing, implementing, and optimizing intelligent applications on the Microsoft Azure platform.