AWS Certified Machine Learning Engineer – Associate validates technical ability in implementing ML workloads in production and operationalizing them. Boost your career profile and credibility, and position yourself for in-demand machine learning job roles.
In this course, you will learn about the fundamental concepts, methods, and strategies for using generative AI. You will gain a solid understanding of use cases where generative AI can provide solutions and address business needs. Additionally, you will learn about practical insights into technologies related to generative AI and how you can use those technologies to solve real-world problems. By the end of the course, you will explore project planning and how to discuss implementation of generative AI in your organization.
Based on Huawei Cloud’s service practices for massive customers, this course presents the theoretical knowledge of cloud architecture design and develops trainees’ hands-on practice capabilities.
This course is designed to introduce generative AI to software developers interested in leveraging large language models without fine-tuning. The course provides an overview of generative AI, planning a generative AI project, getting started with Amazon Bedrock, the foundations of prompt engineering, and the architecture patterns to build generative AI applications using Amazon Bedrock and LangChain.
Discover how Microsoft Copilot for Microsoft 365 elevates workplace productivity and innovation. This experience, tailored for the modern business leader, provides insights on crafting contextual prompts for Copilot and includes engaging use case exercises that showcase seamless integration into daily workflows.
Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Azure Machine Learning and MLflow.
This course introduces fundamental 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. The course is designed as a blended learning experience that combines instructor-led training with online materials on the Microsoft Learn platform.
This course begins by examining the Microsoft Copilot for Microsoft 365 design. Its main focus, however, is on the security and compliance features that administrators must configure in their Microsoft 365 tenant to protect their company’s organizational data before they implement Copilot for Microsoft 365.
This course directs users to learn common prompt flows in Microsoft 365 apps including PowerPoint, Word, Excel, Teams, and Outlook. It also introduces Microsoft 365 Copilot Chat and discusses the difference between work and web grounded data.
This one-day course is composed of two parts – Getting started with Copilot for Microsoft 365 and Empower your workforce with Copilot for Microsoft 365 Use Cases. The first part of the course introduces you to Copilot for Microsoft 365, examines how you can use Copilot throughout the various Microsoft 365 apps, explores best practices for using Copilot and building effective prompts, and examines how you can extend Copilot with plugins and Graph connectors.
The second part of this training content is really the heart of this course. Students perform a series of hands-on exercises involving seven Use Cases – Executives, Sales, Marketing, Finance, IT, HR, and Operations. These exercises focus on using Copilot in various Microsoft 365 apps (such as Word, PowerPoint, Outlook, and so on) to complete a series of common business-related tasks pertaining to each Use Case. To complete the Use Case exercises in this course, each student must have access to a Microsoft 365 subscription (BYOS) in which they’re licensed to use Copilot for Microsoft 365. Each student must also have a Microsoft OneDrive account, since Copilot requires OneDrive to complete the file sharing tasks used throughout the Use Case exercises.
This three-day course is intended for migration engineers who have mastered Huawei cloud migration policies and processes, have knowledge about computing, storage, network, database, container, and middleware usage and migration, and are able to implement cloud migration planning services.
In this course, you will learn to build streaming data analytics solutions using AWS services, including Amazon Kinesis and Amazon Managed Streaming for Apache Kafka (Amazon MSK). Amazon Kinesis is a massively scalable and durable real-time data streaming service. Amazon MSK offers a secure, fully managed, and highly available Apache Kafka service. You will learn how Amazon Kinesis and Amazon MSK integrate with AWS services such as AWS Glue and AWS Lambda. The course addresses the streaming data ingestion, stream storage, and stream processing components of the data analytics pipeline. You will also learn to apply security, performance, and cost management best practices to the operation of Kinesis and Amazon MSK.
