The Azure AI Fundamentals course introduces AI and the Microsoft services students can use to create AI solutions.
This course introduces fundamentals concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. The course is not designed to teach students to become professional data scientists or software developers, but rather to build awareness of common AI workloads and the ability to identify Azure services to support them.
Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. The course will use C# or Python as the programming language.
In this course, the students will explore the objectives of data platform modernization and how it is suitable for given business requirements. The student will learn how to migrate to the three target platforms for SQL based workloads: Azure Virtual Machines, Azure SQL Databases, Azure SQL Database Managed Instances. Student also will learn the benefits and limitations of each target platform, how they can be used to fulfil both business and technical requirements for modern SQL workloads and the available migration tools.
This course will teach the students what is Cosmos DB and how you can migrate MongoDB and Cassandra workloads to Cosmos DB.
This course will enable the students to understand Azure SQL Database, and educate the students on what is required to migrate Open Source Data workloads to Azure SQL Database.
Azure Databricks is a cloud-scale platform for data analytics and machine learning. In this one-day course, you'll learn how to use Azure Databricks to explore, prepare, and model data; and integrate Databricks machine learning processes with Azure Machine Learning.
In this one-day course, students will learn the fundamentals of database concepts in a cloud environment, get basic skilling in cloud data services, and build their foundational knowledge of cloud data services within Microsoft Azure.
Gain the necessary knowledge about how to use Azure services to develop, train, and deploy, machine learning solutions. The course starts with an overview of Azure services that support data science. From there, it focuses on using Azure's premier data science service, Azure Machine Learning service, to automate the data science pipeline.
In this course, the students will design various data platform technologies into solutions that are in line with business and technical requirements. This can include on-premises, cloud, and hybrid data scenarios which incorporate relational, NoSQL, or Data Warehouse data. They will also learn how to design process architectures using a range of technologies for both streaming and batch data. The students will also explore how to design data security, including data access, data policies, and standards. They will also design Azure data solutions, which includes the optimization, availability, and disaster recovery of big data, batch processing, and streaming data solutions.
This course provides students with the knowledge and skills to administer a SQL Server database infrastructure for cloud, on-premises and hybrid relational databases and who work with the Microsoft PaaS relational database offerings. Additionally, it will be of use to individuals who develop applications that deliver content from SQL-based relational databases.
Prices do not include VAT. OKsystem a.s. reserves the right to change dates and prices of courses.