Content Of The eCourse Big Data

The Content Of The Big Data eCourse On Laudius Platform

The Big Data eCourse is in Dutch and on the Laudius platform. The Big Data eCourse consists of 7 lessons and an exam. The last one is an extra option. The 7 lessons have the same structure:

• Introduction

• Learning goals --> The take aways that should be remembered about these lessons

• Tips --> Extra information about the subject of the lesson

• Homework --> The homework consists of questions about the theory and some lessons have cases in which the Big Data analysis can be practiced.

Homework

Homework can be corrected by me or the other teacher if the option correct homework is chosen. Then the homework will be graded with a grade between 1 – 10. Afterwards a certificate of Laudius can be given if the average grade is 5,5 or higher.

Exam Big Data

After finishing the eCourse Big Data there is also an option exam. If this is chosen an open book exam is taken by the student. The exam consists of multiple-choice questions and cases. If the grade is 5,5 and higher the student gets a Laudius diploma.

Word List

The word list consists of all terms about Big Data that are mentioned in all 7 lessons.

Real Stat Excel Add-On

Real stat is a free Excel add-on the student can download to perform all the Big Data analysis in this eCourse. The Real stat add-on is installed in Excel. The analysis can also be done with SPSS, R or Python. It is recommended to put in the homework that another program than Excel was used to make the homework assignment.

Forum

There is a Big Data Forum in which the student can find more additional information about Big Data and can talk to each other about Big Data. It is recommended to visit this Forum frequently.

Book ‘Succes met Big Data’

All the lessons are based on the book ‘Succes met Big Data’. The book is included in the price. Each lesson uses a few chapters of the book combined with additional information about Big Data.

Lesson 1 Find A Way In The Big Data eCourse

Lesson 1 is there for the student to get to know the eCourse Big Data and how everything works during the eCourse. There are pdfs about:

• How to use the platform

• How to send in homework and the cases

• How to email the teachers

• How to use the forum

• Where to find the lesson materials

Also there are 2 introduction videos about the two teachers. I am one of the teachers. The student hands in homework if this option is chosen. For lesson 1 it is an easy one, because the student just have to send in: 'I have read everything and have no questions or asks a question'.

Lesson 2 Big Data

In lesson 2 chapter 1 ‘Inleiding’ and chapter 2 ‘Big Data’ of the book ‘Succes met data’ is recommended to be read. In this lesson the student learns what, how and who in Big Data. This lesson has homework consisting of questions about the theory.

Lesson 3 Storage And Processes

In lesson 3 chapter 3 ‘Opslag’ and chapter 2 ‘Proces’ of the book ‘Succes met data’ is recommended to be read. In this lesson the student learns about data, information, storage, and predictive analyses. This lesson has homework consisting of questions about the theory.

Lesson 4 Decision Tree

In lesson 4 chapter 5 ‘Beslisboom’ and chapter 6 ‘Neurale netwerk’ of the book ‘Succes met data’ is recommended to be read. In this lesson the student learns about making a decision tree and neural network. There is a bonus video explaining how to make a decision tree in Excel. CANVAS can also be used to make a decision tree. This lesson has homework consisting of questions about the theory and a case in which the student makes 4 different decisions trees.

Lesson 5 Cluster Analyses & Regression Analyses

In lesson 5 chapter 7 ‘Clusteren’ and chapter 8 ‘Lineaire regressie’ of the book ‘Succes met data’ is recommended to be read. In this lesson the student learns about doing cluster analysis and Linear Regressions. There are bonus videos and pdfs explaining:

• Video explaining Cluster analyse

• Video explaining Hoe Real Stat te installeren

• Video explaining Meten en onderzoek

• Video explaining Spreidingsmaten en centrummaten

• Video explaining Rekenen in Excel

• Video explaining  Multiple regressie

• PDF Foutmelding VBA Run Time Error 424 Object required

• PDF Problemen met Real stats Excel 2019 en Excel 365

• PDF Regressie analyse uitleg

• PDF Spreidingsmaten en centrummaten

• PDF Meten en onderzoek

This lesson has homework consisting of questions about the theory and two cases in which the student makes K-means cluster analyses and a multiple linear regression analyses. For both there is a dataset to be downloaded and used for the analysis.

Lesson 6 Nearest Neighbor Analysis And Rules Derivation

In lesson 6 chapter 9 ‘Naaste buur’ and chapter 10 ‘Regels afleiden’ of the book ‘Succes met data’ is recommended to be read. In this lesson the student learns about Nearst neigbor analysis and rules derivation. There is a bonus video explaining how to do a Nearest neighbor analysis in Excel. This lesson has homework consisting of questions about the theory and a case in which the student does a Nearest neighbor analysis.

Lesson 7 Sense And Nonsense Of Big Data, Ethics In Big Data

In lesson 7 chapter 11 ‘Zin en Onzin Big Data’ and chapter 12’ Ethiek Big Data’ and Chapter 13 ‘Uitleiding’ of the book ‘Succes met data’ is recommended to be read. In this lesson the student learns about ethics in Big Data and the sense and nonsense of Big Data. This lesson has homework consisting of questions about the theory.

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