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IDM summary and lecture notes!!

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This document concludes a summary of chapters used for the midterm, lecture notes of all powerpoints used for the midterm, and some python notes from the tutorials and lectures (week 1&2). In the end, it provides a clear overview of all materials used for the midterm.

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  • Chapter 1,3,10
  • February 23, 2021
  • 41
  • 2020/2021
  • Summary
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INFORMATION AND DATA MANAGEMENT
This link will provide information that goes more into depth than the IDM course for current
and future reference: https://docs.python.org/3/tutorial/

Software: For the course, we will use the integrated development environment (IDE) Google
Colab, which is entirely browser-based and available online for free, so you do not need to
install anything. You can access it via this link: https://colab.research.google.com/

The first half will focus on common information technologies for consumers and for businesses,
while the second half will focus on data science technologies.

Bonus project
For this course, it is possible to earn 1 bonus point by participating in a project. The project will
start after the midterm and will focus on applying the knowledge from the course in business
settings. The level of the project will be more advanced than the level of the overall course, but
we will provide support to you via Slack.
 Participation is optional, but by successfully completing the project, you will be able to
earn 1 bonus point for your final grade.

We will be using chapters from free online books and articles:
For Information Systems Topics:
 Bourgeois, David, T. Information Systems for Business and Beyond, Published through
OpenText book Challenge by the Saylor Academy:
https://open.umn.edu/opentextbooks/textbooks/information-systems-for-business-
and-beyond
 Brynjolfsson & Mcafee: The Business of Artificial Intelligence
 Iansiti & Lakhani: The Truth About Blockchain
 Unwin - Good Graphics?

For Python, the following books are available for free online and may be considered as
additional resource, while the primary class material is made of the knowledge clips and
accompanying notebooks.:
 Sweigart, A. (2019). Automate the Boring Stuff with Python, 2nd Edition. No Starch
Press, Incorporated.
o ISBN-13: 9781593279929
o However, instead of buying the hardcopy or eBook, you can also use the online
version, which is available for free and includes useful summary videos for most
chapters:
o https://automatetheboringstuff.com/
 VanderPlas, J. (2016). Python Data Science Handbook
o This book is available online for free as well
o https://jakevdp.github.io/PythonDataScienceHandbook/

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,Every week there will be two lectures and one tutorial, which all build on each other.
 The weekly programming and application lecture (P&A) is a programming and
application lecture that will be used to outline the underlying theory in detail and to
ensure an in-depth understanding of the topic by demonstrating applications of the
theoretical concepts covered . This lecture will be accompanied by pre-recorded
knowledge clips, which are recommended to watch before attending the lecture.
 The weekly topic lecture is used to introduce a new Information Systems topic in a
holistic way that combines the perspectives of management, technical staff and, if
applicable, consumers.
 In the tutorials, the concepts gained from the lectures will be practiced and applied to
ensure that you will be able to make use of the concepts covered in the course in
business and academic research.
 Accordingly, the two weekly lectures and the tutorial are interlinked topically. We
recommend that you always attend all three of them to ensure that you understand the
material in full.

Assessment
The course grade is based entirely on the following two partial examinations:
 A midterm examination (written closed-book examination with multiple choice
questions; two hours), which will account for 30% of the final grade
• Date: Friday, February 26th. This is subject to change.
 A final examination (written closed-book examination with multiple choice questions;
two hours), which will account for 70% of the final grade
• Date: Wed, March 24th. This is subject to change.




2

,3

,Table of Contents
LECTURE 1 – INTRODUCTION (MODULE 1: 03-02-21)............................................................................................ 6
LECTURE 1 - PYTHON........................................................................................................................................... 7
LECTURE 2 – SYSTEM ENGINEERING AND ARCHITECTURE. (MODULE 1: 09-02-21)...............................................11
LECTURE 2 – PYTHON........................................................................................................................................ 37
MIDTERM MATERIALS....................................................................................................................................... 41




4

,Lecture 1 – Introduction (module 1: 03-02-21)
Lecture notes:
Introduction to Information and Data Management !!!
Challenge no. 1
 Business and IT – people come from different cultures, have different interest, talk
“different” languages, etc.
 We need professionals that understand both world and can bridge the gap between
these worlds
 We need IT that accomplishes the business strategy

Challenge no. 2
And we have data – a lot of data Drivers of change




Changing business models




Why you should learn Python:
 Perfect for Rookies
 Community
 Career opportunities
 Python in Web development
 Python in AI and Machine Learning

5

,  Raspberry Pi
 Startups and Corporates-Python for Both
Lectures > Technical theory
Tutorials > Practice in programming with Python

Applicable know-how in Programming
How to learn?
- By trying, typing code on your own and failing and trying again

Tools
 Google Colab
 Python | 3.7+


Lecture 1 - PYTHON
Lecture notes:
PYTHON an Introduction




Interpreter and Compiler
 Python is a high-level language intended to be relatively straightforward for humans to
read and write and for computers to read and process.
 The CPU understands a language we call machine language.

Since machine language is tied to the computer hardware, machine language is not portable
across different types of hardware. Programming language translators fall into two general
categories:
1. Interpreter
An interpreter reads the source code of the program as written by the programmer, parses
the source code, and interprets the instructions on the fly. Python is an interpreter

2. Compiler


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