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Teacherbot 28 Jan, 04:11:01

Introduction

Lets begin by introducing students to the fundamentals of data analytics and machine learning. Provide students with a brief overview of what data analytics and machine learning mean. By the end of this lesson, students will be able to explain the purpose and importance of data analytics and machine learning, and how it is used in different industries.

Lesson Outline

  1. Video Introduction to Data Analytics - show students a brief video introducing the different nuances of data analytics and the importance of understanding data (https://www.youtube.com/watch?v=2XVZ-CRkmFA).

  2. Data Analytics Procedure - go through a step-by-step procedure on how data analytics works (https://www.kdnuggets.com/2018/01/data-analytics-process.html).

  3. Machine Learning Introduction - provide students with an overview of machine learning (https://www.youtube.com/watch?v=NGf0voTMlcs).

  4. Machine Learning Algorithms - introduce students to the various algorithms that are used in machine learning such as linear regression, decision trees, and neural networks.

  5. Applications of Machine Learning - discuss examples of how machine learning is used in different industries (https://www.sciencedirect.com/science/article/pii/S1877050917316668).

Questioning

When providing students with an introduction to data analytics and machine learning, use key questioning throughout the lesson. Ask students to explain the purpose of data analytics, how machine learning works, and provide examples of how the two are used in different industries.

Assessment

At the end of the lesson, assess student’s understanding by having them complete a worksheet or quiz using of the following resources:

  1. Data Analytics Worksheet - have students complete a worksheet that assesses their understanding of data analytics (https://www.kdnuggets.com/2018/04/data-analytics-worksheet.html).

  2. Machine Learning Quiz - have students complete a quiz on machine learning (https://www.kdnuggets.com/2019/01/machine-learning-quiz.html).

Differentiation

When differentiating the lesson for students with different levels of understanding, provide more in-depth resources for those who need additional practice. For example, provide more detailed videos on machine learning or additional tutorials for those students who need extra help.

Plenary

To conclude, ask students to provide examples of how data analytics and machine learning are used in different industries. Ask students to think of one example of how data analytics can be used to improve a business process and one example of why machine learning is important for companies.