Csharp ecosystem. Learn to automate infrastructure deployment using Azure Resource Manager (ARM) templates or Terraform for infrastructure-as-code, ensuring reliable and repeatable environment setups. Leverage Azure Cognitive Services such as Personalizer and Azure Machine Learning to build applications delivering highly personalized, client-specific experiences. Build adaptive, real-time data processing systems with Azure Event Hubs and Stream Analytics. Implement intelligent enterprise search solutions using Azure Cognitive Search and create graph-based data models with Azure Cosmos DB’s Gremlin API.
Develop continuous integration and continuous deployment (CI/CD) pipelines using Azure DevOps or GitHub Actions to keep applications updated and performant.
Transform software development by packaging intelligent capabilities as distributed microservices deployed using Azure Functions (serverless computing) or containerized with Azure Kubernetes Service (AKS). Seamlessly integrate pre-built AI and cognitive services like Azure Computer Vision (image/video analysis), Azure Text Analytics (NLP), and Azure Form Recognizer (document processing) directly into your applications via simple API calls.
It is designed to validate the knowledge, skills, and competencies of individuals in a specific area of study or professional field. The certification program is meticulously designed to ensure that candidates have acquired a comprehensive understanding of the subject matter. It encompasses both theoretical knowledge and practical application, allowing candidates to demonstrate their expertise in real-world scenarios.
Strategically coordinate AI services using an Azure Data Lake built on Azure Blob Storage as a central repository for your data. Foster collaboration between data science and engineering teams through Azure Machine Learning Studio (an integrated development environment), Azure Machine Learning Feature Store, and Azure DevOps for shared workflows, version control, and continuous integration/continuous deployment (CI/CD). Understand how to leverage AI tools and frameworks in the Microsoft ecosystem to solve complex problems and improve data-driven decision-making. Gain practical skills in data preprocessing, feature engineering, and algorithm selection using C# and Azure ML SDK. Globally advance AI capabilities by deploying solutions across AWS's global infrastructure (AWS Regions & Availability Zones) to ensure low-latency and compliance. Address high-value challenges by combining the full breadth of AWS AI Services, SageMaker, and big data analytics tools like Amazon EMR and AWS Glue to create comprehensive, client-centric solutions.
.jpg)
