TRAINING ROADMAP

Upcoming Online Lectures, Labs and Learning Paths


  • Implementing Azure DNS

    The Domain Name System, or DNS, is responsible for translating (or resolving) a service or server name to its IP address. Azure DNS is a hosting service for DNS domains, providing name resolution using the Microsoft Azure infrastructure. In addition to supporting internet-facing DNS domains, Azure also supports DNS for cloud and hybrid networks.
    This course provides in-depth guidance on using DNS in Azure, covering both public and private DNS deployment, configuration and management.
    As a starting point, students are introduced to DNS (Domain Name System) fundamentals, as well as the various DNS services and features in Azure. Next, students are guided through the registration, delegation, and hosting of public DNS zones using Azure DNS, together with DNS record management. Public DNS management is concluded with a discussion of sub-zones and DNS zone file import and export.
    Students are then introduced to the Azure features for managing DNS in private and hybrid networks. This includes learning which scenarios support Azure DNS private zones and when to use dedicated name servers, together with deployment and configuration details for both approaches.
    The course concludes with a discussion of DNS operations. Students learn how to configure DNS management role-based access control, prevent accidental DNS changes, how to monitor key Azure DNS metrics, and how to set up alerts. Finally, advanced topics include DNS zone backup and recovery, and how to deploy a redundant DNS zone co-hosted with an external provider for maximum resilience to DNS outages or DDoS attacks.     

  • Unmasking DevOps

    This course is designed for IT leaders trying to understand how to create a culture of DevOps in their organization. We start off by getting a broad understanding of DevOps and how it fits into the software development life cycle. We’ll cover DevOps values and priorities, which focus on people, process, and technology.
    Then, we will look at how to design your organization’s culture with DevOps in mind through encouraging teamwork, reducing silos, and embracing failure.
    After that, we will learn how to identify waste and locate bottlenecks along your software development life cycle to locate the easiest (and most immediate) wins for your DevOps transformation.
    Then, we’ll cover how to persuade your colleagues, from executives to engineers, of the benefits of DevOps.
    This course will wrap up by looking at how to measure your work and track your DevOps successes, allowing everyone to see the incremental improvements along the way.
    A DevOps transformation is no small feat, nor is it an overnight process. It will take hours of planning, honest conversations, brainstorming, reflection, and technical changes. This course will teach you how to unlock the early principles by learning and thinking about your everyday work from a different perspective. The DevOps journey is just as valuable as the outcome.

  • Dynamics 365 Fundamentals

    Dynamics 365 is a family of Business Applications. This course provides an overview of the functionality provided by Dynamics 365 Apps to provide a foundational level of knowledge of their capabilities and how the Apps are provided by Microsoft.
    We start off by looking at the various Dynamics 365 Apps and the Power Platform. 
    We then move on to a more detailed look the Apps for Customer Engagement, including what is involved in purchasing, deployment and support.
    We then switch attention to the Apps for Unified Operation, again what is involved in purchasing, deployment and support.
    This course will wrap up by at Cloud Concepts These concepts are not specifically about Dynamics 365 but as Software as a Service applications, it is important to understand and be able to articulate these concepts.

  • MS-300: Configure and Manage OneDrive for Business

    Students will learn how to connect clients to all their files in Office 365, enabling the ability to share and work from anywhere in a secure environment. This course will deliver a experience of adoption for the attendees, getting to know the deeps and tricks of OneDrive for business and the benefits that come with the platform.

  • Security Fundamentals

    This course provides an overview of Defense in Depth security challenges and strategies of mitigation in the information systems environment. Topics include definition of security terms, security concepts, elements, and goals incorporating industry standards and practices with a focus on confidentiality, availability, and integrity fundamentals of information systems for Systems Administrators.

  • Power BI for Data Professionals

    This course covers using Power BI Desktop to create and deploy datasets and reports as well as deploying, sharing, and securing assets in PowerBI.com. 
    We will start off by reviewing the components of the Power BI ecosystem. Then we will begin to build a model in Power BI Desktop by acquiring data using Power Query/M. Next, we will shape and model the data using M and DAX. Then we will build calculations to support analysis and reporting. 
    Once we have a working dataset, we will build a report using default and custom visuals, buttons, and bookmarks. Then we’ll add dynamic row-level security roles.  
    Next, we’ll explore various ways to deploy and share the data model and the report in PowerBI.com. This will include organization of workspaces, user roles within the workspace, row-level security, and use of Power BI apps. We will also look at scheduling the refresh of data in imported and composite datasets. 
    The course will wrap up by looking at some re-usability and lifecycle management techniques including version control, pre-production environments, use of shared and certified datasets, and suggested quality checks before deploying to production. 

  • MS-300: Configure and Manage Workload Integrations

    This course will help you prepare for the exam MS-300: Deploying Microsoft 365 Teamwork by covering the basics of configuring and managing workload integrations in Microsoft 365. This four-module course will cover integrating M365 workloads (such as Office 365 connectors, Flow and PowerApps, etc.), enabling document support for Yammer, managing Stream, and integrating M365 workloads with external systems (such as PowerBI, line of business systems and monitoring usage and licensing).

  • Azure Monitoring and Operations

    This course will cover the history of monitoring in Azure, demystify what all the Azure native monitoring tools look like, provide guidance on when to use what + why or when, walk through Azure Monitor Alerts (metrics and diagnostics), dive into Log Analytics/Kusto Query Language (KQL), discuss parts of the former OMS, dig into Azure Backup + Azure Site Recovery, go over Azure Automation, and explore Application Insights.

  • Azure SQL Database Concept Overview: Course One of Introduction to Azure SQL Database

    Course 1 provides the conceptual backdrop of setting the stage for Azure SQL Database as a contender and enterprise premium workload.   This course covers the concepts and service tier definitions for Azure SQL Database, providing a formal launch point for additional course study on this feature set. 

  • Azure SQL Database Security: Course Two of Introduction to Azure SQL Database

    Course 2 guides participants through Azure SQL Database Security Concepts, including Role-base Access Control (RBAC) and a survey of the Security Advisory Tools Azure provides as part of the overall feature set.   In addition, this course introduces Row Level Security and Dynamic Data Masking to round out.

  • Azure SQL Database Tooling and Management: Course Three of Introduction to Azure SQL Database

    Course 3 takes participants on a tour of Azure SQL Database management, showcasing various Azure SQL Tooling options and focusing on the considerations for integration and management of an Azure SQL Database instance.

  • Azure SQL Database Monitoring and Data Encryption: Course Four of Introduction to Azure SQL Database

    Course 4 discusses various database monitoring and data encryption options provided within Azure SQL Database.  Monitoring options include a brief introduction to Extended Events with a particular focus on popular encryption options like storage-level Transparent Data Encryption and client-side Always Encrypted column-level encryption are covered.

  • Azure SQL Database Elastic Scaling: Course Five of Introduction to Azure SQL Database

    Course 5 is a tour into Azure SQL Database Elastic Scaling and guidance for decisions on proper usage of Elastic Pools vs Instances when configuring Azure SQL Database for desired performance goals.

  • Azure SQL Database High Availability and Disaster Recovery: Course Six of Introduction to Azure SQL Database

    Course 6 discusses Azure SQL Database options providing various levels of HADR capability through platform configuration.  On entry, participants will get exposure to the backing roles that MSFT and Deployment Teams take in HADR, conceptual considerations and requirements., evolving into a tour of what Azure SQL Database brings to the table to simplify and promote reduced downtime and near-zero data loss on an existing enterprise grade SLA.  In addition, client-side design implications are discussed in terms of building advanced fault tolerance capability as a pre-configpluggable. 

  • Azure SQL Database Sizing and Performance: Course Seven of Introduction to Azure SQL Database

    Course 7 discusses various sizing and performance options available.  Participants will consider options, match to basic performance scenarios engaging both with Azure Performance Advisor Tools as well as manual adjustments to fit specific custom requirements.  

  • AWS Certified DevOps Engineer

    The AWS Certified DevOps Engineer - Professional exam tests the candidate's technical expertise in provisioning, operating, and managing distributed application systems on the AWS platform. For this exam, you should know how to:

    Implement and manage continuous delivery systems and methodologies on AWS. Understand, implement, and automate security controls, governance processes, and compliance validation. Define and deploy monitoring, metrics, and logging systems on AWS. Implement systems that are highly available, scalable, and self-healing on the AWS platform. Design, manage, and maintain tools to automate operational processes.

    This course is designed to provide you with the knowledge and skills required to pass the AWS Certified DevOps Engineer - Professional exam and to successfully apply these skills in the workplace.

  • Define and Prepare the Development Environment: Course One of DP-100 Exam Preparation

    The student will learn how Azure services can support the data science process. They’ll explore common architectures, learn to assess business goals and constraints for determining the correct environment, and setup the relevant development environments to support data science deployments in Azure.

  • Prepare Data for Modeling: Course Two of DP-100 Exam Preparation

    The student will learn how to prepare tabular datasets ready for modeling. Integrating data from multiple sources, understanding relationships inside the data, and cleansing issues where possible are important tasks for building robust statistical models. These techniques will be taught in Azure DataBricks using common Python libraries and Microsoft developed libraries like the Azure Machine Learning Data Prep SDK.

  • Perform Feature Engineering: Course Three of DP-100 Exam Preparation

    The student will learn how develop effective and reusable features ready for modeling. Using manual techniques and then automated techniques, the data scientist will be able to handle core data types using SciKit-Learn and Microsoft Python libraries like MMLSpark and Azure Machine Learning Data Prep SDK.

  • Develop Models: Course Four of DP-100 Exam Preparation

    The student will learn how develop robust models. Starting from selecting the right metric to meet business goals, through to building tuned models, and then evaluating the models produced for fitness.