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At the end of this course, participants will be able to:

• Use the various modules and features of Dynamic 365 CRM, such as Sales, Customer Service, Marketing, Field Service, and Project Service Automation.
• Gain hands-on experience and guidance.
• Review the technical requirements and what’s needed to get your organization AI-ready.
• Understand Microsoft’s approach to responsible AI and how it applies to Dynamics 365 CRM copilot.
• Integrate copilot with Outlook and Teams for better data management.
• Utilize the generative AI capabilities of copilot for record summarization and email content generation.

• A Deeper understanding of work trends, on Prompt Engineering concepts and of Microsoft’s approach to Responsible AI.
• A deeper understanding of the underlying components of Microsoft 365 Copilot.
• A Deeper understanding of practical applications of Microsoft 365 Copilot in Word, PowerPoint, and Excel, Outlook, Teams Meetings, and Teams Chat and Loop and Microsoft 365 Chat
• A deep understanding of the new ways to complete a task and of practical uses of Copilot for key personas.

At the end of this training, the participants should be able to:

• Understand the functionality and operation of Copilot.
• Recognize the various use cases and scenarios where Copilot can be applied.
• Utilize Copilot within specific Microsoft 365 applications.
• Create code, content, and solutions through the assistance of Copilot.
• Assess and enhance the quality and appropriateness of Copilot's recommendations.
• Adhere to ethical and legal standards by implementing best practices and guidelines when using Copilot.

By the end of the training, learners should be able to: 

• Understand and apply fundamental concepts of security and risk management.
• Identify and classify information and assets.
• Design secure architecture and engineering solutions.
• Analyze and protect network security.
• Implement identity and access management (IAM) systems.
• Plan and conduct security assessment and testing.
• Operate and maintain a secure environment.
• Apply security principles to software development.

At the end of this course, participants should be able to:

• Work with functions.
• Work with lists.
• Analyze data.
• Visualize data with charts.
• Use pivot tables and pivot charts.
• Work with multiple worksheets and workbooks.
• Use lookup functions and formula auditing.
• Share and protect workbooks.
• Automate workbook functionality.
• Create sparklines and mapping data.
• Forecast data.

• Use Python to create code that reads data from sensors and stores it in a SQL database.
• Visualize, clean, manipulate and integrate data sets.
• Learn fundamental principles of Big Data platforms like Hadoop.
• Use storytelling to present insights gained from extracted data.

At the end of this course, participants should be able to:

• Identify common data formats.
• Describe options for storing data in files.
• Describe options for storing data in databases.
• Describe characteristics of transactional data processing solutions.
• Describe characteristics of analytical data processing solutions.

At the end of this course, the participants should be able to:

• Plan and implement data platform resources.
• Implement a secure environment.
• Monitor, configure, and optimize database resources.
• Configure and manage automation of tasks.
• Plan and configure a high availability and disaster recovery (HA/DR) environment.

By the end of this course, participants should be able to:

• Build a simple end-to-end cloud application using AWS Software Development Kits (AWS SDKs), Command Line Interface (AWS CLI), and IDEs.
• Configure AWS Identity and Access Management (IAM) permissions to support a development environment.
• Use multiple programming patterns in your applications to access AWS services.
• Use AWS SDKs to perform CRUD (create, read, update, delete) operations on Amazon Simple Storage Service (Amazon S3) and Amazon DynamoDB resources.