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Course Syllabus

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Thank you for telling us a little bit about yourself. We hope this course will be an enjoyable learning journey for you.

Course Outcomes

The following are the course learning objectives:

  1. Recognise when and where data is generated
  2. Describe the different formats of data storage available in Microsoft Azure
  3. Explain the difference between relational and non-relational storage
  4. Report on the contents of a data store, through the use of SQL
  5. Identify when a data problem is one of big data
  6. Describe options for accessing and reporting on data within Azure data stores.

Course Components

This course is composed of the following elements:

  • Content Topics – text-based content, graphics, references and notes.
  • Videos/Demos – short videos that explain concepts and key areas of learning.
  • Tutorials (Labs) – are located throughout the course. These are practical exercises and contain information on completing the exercises. These labs are for learning purposes only and are not graded.
  • Knowledge Checks/Review Quizzes – are located at the end of each lesson and check your general understanding of the key concepts. These are ungraded quizzes and do not count toward your final course grade.
  • CloudSwyft Hands-On Labs – are aligned to the content of the course to provide the best digital learning experience.
  • Digital Certificate and/or CloudSwyft Hands-On Lab Badge – these are awarded upon meeting all the course requirements for completion and achieving the required pass grade.

CloudSwyft Hands-On Labs

This course uses a mix of engaging lectures, information and hands-on activities to working with data and applying the techniques you’ve learned. There are structured hands-on components throughout this course to supplement the course material and apply learning knowledge.

A practical lab environment will be set up for you, with all the prerequisite software components and practical lab exercises, to complete the practical assignments and Hands-On Labs. You will not be required to download and/or install any additional software on your computer to complete the exercises.

Completing your course

To be eligible to gain certificates at both individual course levels, you need to:

  • mark over 90% of steps as complete across the entire course
  • attempt every assessment question
  • score an average of at least 70% across all your assessments.

Guidelines for Completing the Course

Here are some guidelines for getting through and completing this course:

  • Ensure you can access the required Hands-On Lab environment to complete the practical exercises.
  • Set deadlines for completing your tasks. These tasks include watching videos, reading reference materials, or completing practical exercises and Hands-On Labs.
  • Check the Activity area regularly for any feedback, questions, or comments from other learners. Make a point of connecting with other students and exchanging ideas.
  • Make an actual effort to answer each of the Section/Week Review questions on your own before you view the answer.
  • Read or skim through any supplemental information or Help pages that the course material refers to if you have time.

Disclaimer

Due to the ever-changing and fast-evolving nature of the cloud, data, and AI products, there may be inconsistencies in language and terminology. We aim to keep the course content up to date and consistent and will do our best in this regard.

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Microsoft Future Ready: Fundamentals of Big Data

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