Microsoft Azure AI Engineer Certification

Why Choose Garranto Academy for Your Azure AI Engineer Training?

Choose Garranto Academy for your Azure AI Engineer training to benefit from expert instructors, hands-on labs, and a comprehensive curriculum, ensuring you acquire the practical skills and knowledge to excel in the field of AI engineering.

Course Overview:

The "Microsoft Azure AI Engineer Certification" is an intensive two-day program designed to prepare professionals for the Azure AI Engineer certification. This course provides a thorough exploration of Azure AI services, focusing on practical applications of computer vision, natural language processing, and generative AI. Participants will engage in hands-on exercises with Azure AI Vision, natural language processing solutions, and Azure OpenAI Service, gaining practical experience in developing and implementing knowledge mining solutions and document intelligence models. Combining theoretical insights with practical application, the training equips attendees with the skills needed to leverage Azure's AI capabilities effectively across various enterprise contexts, ensuring they are well-prepared for real-world challenges and certification.

What You'll Learn in Our Azure AI Engineer Certification Course:

Course Objectives:

• Understand Azure AI Services: Gain a foundational understanding of AI and how it integrates with Azure services, including getting started with Azure AI and its applications for enterprises.

• Develop Computer Vision Solutions: Learn to analyze images and videos, detect and recognize faces, and create custom vision models using Azure AI Vision.

• Implement Natural Language Processing: Develop solutions for text analysis, translation, question answering, conversational language understanding, and speech recognition.

• Utilize Generative AI: Get hands-on experience with Azure OpenAI Service, including prompt engineering and developing applications.

• Create Knowledge Mining Solutions: Implement intelligent search solutions, create custom skills, and develop a knowledge store.

• Develop Document Intelligence Solutions: Work with prebuilt and custom document intelligence models to enhance data processing and analysis.

Prerequisites:

• No prior experience in AIOps is required, making the course accessible to professionals from various backgrounds.

• A basic understanding of IT operations and familiarity with data analysis concepts is recommended but not mandatory.

Course Outline:

Module 1: AIOps Foundation

• Introduction to AIOps: Definition, Scope, and Importance

• Key Concepts and Principles of AIOps

• The Evolution of IT Operations to AIOps

Module 2: AIOps in the Organization

• The Role of AIOps in Modern IT Operations

• Integrating AIOps into Existing IT Infrastructure

• Organizational Benefits of Adopting AIOps

Module 3: Core Technologies - Data

• Understanding Big Data in the Context of AIOps

• Data Collection, Processing, and Management for AIOps

• The Role of Data Lakes and Data Warehouses

Module 4: Core Technologies - Machine Learning (ML)

• Introduction to Machine Learning and Its Applications in AIOps

• Supervised vs. Unsupervised Learning for IT Operations

• Hands-On Activity: Basic ML Algorithms for AIOps

Module 5: AIOps and Operations Metrics

• Key Performance Indicators (KPIs) and Metrics in AIOps

• Monitoring and Measuring IT Performance Using AIOps

• Real-Time Analytics and Predictive Insights

Module 6: AIOps Use Cases and Organizational Mindset

• Real-World AIOps Use Cases Across Industries

• Developing an AIOps-Ready Organizational Culture

• Group Discussion: Challenges and Solutions in AIOps Adoption

Module 7: Evaluating AIOps’ Impact

• Assessing the Business Value of AIOps Implementations

• Case Studies: Successful AIOps Deployments

• Interactive Session: ROI Analysis for AIOps Projects

Module 8: Implementing AIOps in the Organization

• Step-by-Step Guide to Implementing AIOps

• Aligning AIOps Strategies with Business Goals

• Hands-On Workshop: Designing an AIOps Implementation Plan

Recap and Review

• Summary of Key Concepts and Takeaways

• Q&A Session and Final Discussions

Course Outcomes:

Upon completion of the "Microsoft Azure AI Engineer Certification" course, participants will be able to:

• Demonstrate a comprehensive understanding of AIOps and its role in modern IT operations.

• Possess the ability to leverage core AIOps technologies, including big data and machine learning, to address IT challenges.

• Be equipped with practical knowledge to implement AIOps solutions that drive operational efficiency and business value.

• Be capable of evaluating the effectiveness of AIOps strategies and making data-driven improvements.

• Hold the foundational knowledge required to pursue the Certified AI Ops Foundation certification.

Key Benefits of Becoming a Microsoft Azure AI Engineer:

Gain a competitive edge by becoming a Microsoft Azure AI Engineer, leveraging advanced AI tools and cloud technologies to design intelligent solutions, enhance decision-making, and drive innovation.

How Azure AI Engineering Can Transform Your Business Operations?

Azure AI Engineering revolutionizes business operations by automating processes, deriving actionable insights from data, and enhancing customer experiences with cutting-edge AI technologies and solutions.