Inhalt
[ 986CABUDACS24 ] SE MS1: Data, Algorithms and Coding
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Workload |
Education level |
Study areas |
Responsible person |
Hours per week |
Coordinating university |
3 ECTS |
M1 - Master's programme 1. year |
Business Administration |
Thomas Gegenhuber |
2 hpw |
Johannes Kepler University Linz |
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Detailed information |
Pre-requisites |
SE BC2: Induction: Team development UND SE BC1: Foundations of management UND KS BC3: Foundations of management science
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Original study plan |
Master's programme Leadership and Innovation in Organizations 2024W |
Objectives |
- Understand the Fundamentals of Programming: Students will learn the basics of a general-purpose programming language, covering variables, data types, control structures, functions, and basic data structures. This knowledge lays the groundwork for understanding more complex programming concepts and practices.
- Develop Problem-Solving Skills: Through practical coding exercises, students will apply algorithmic thinking to solve problems. This skill is crucial for understanding how algorithms are designed, optimized, and implemented in software development projects.
- Master Data Management Principles: The course will cover the principles of data management, including how data is stored, retrieved, and manipulated within software applications. This understanding is key to managing projects that involve large datasets and require efficient data processing algorithms.
- Facilitate Effective Communication with Technical Teams: Through case studies and collaborative projects, students will practice defining project scopes, requirements, and timelines in a manner that is clear and understandable to programmers. This includes learning the language of software development to write concise and comprehensive project briefs.
- Appreciate the Digital Logic of Algorithms and Coding: By engaging in coding exercises, students will gain insights into the logical foundations of digital technologies, enhancing their ability to make informed decisions in the context of digital transformation initiatives.
Learning Outcomes
On successful completion of this course, the students will be able to:
- LO1: Communicate Effectively with Programmers: Demonstrate the ability to articulate project requirements, estimate task durations, and understand coding efforts in a manner that fosters clear and productive communication with programming teams.
- LO2: Understand Programming Fundamentals: Gain a foundational understanding of a programming language such as Java or Python, including syntax, variables, control structures, functions, and basic data structures.
- LO3: Apply Problem-Solving Skills in Coding: Utilize algorithmic thinking to design, write, and debug simple programs, translating theoretical problems into practical coding solutions.
- LO4: Manage Data Efficiently: Understand and apply the principles of data management, including data storage, retrieval, and manipulation within software applications, to enhance decision-making in digital projects.
- LO5: Appreciate the Logic Behind Algorithms and Coding: Develop an understanding of the digital logic underpinning software development, enabling informed decision-making and strategic thinking in digital transformation initiatives.
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Subject |
This course is an integral component of our program, aimed at equipping students with a foundational understanding of the digital transformation landscape through a focused exploration of data management, algorithms, and coding practices. It recognizes the importance of bridging the communication gap between management and technical teams.
Students will gain insights into the world of software development, learning how to effectively communicate project requirements, understand the complexities involved in coding tasks, and estimate the time and effort needed for their completion. This goal addresses the critical need for managers to articulate their needs in a way that is precise and actionable for coding professionals, fostering a collaborative work environment.
By engaging directly with a programming language such as Java or Python, students will gain some insight into the the syntax and structure of coding but also develop an appreciation for the logical thinking behind algorithm design. This hands-on experience is vital for understanding the intricacies of software development, enabling students to appreciate the challenges and considerations involved in translating business requirements into functional digital solutions.
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Criteria for evaluation |
The course uses following grading system:
Points | Grade |
100 – 87 | 1 |
86 – 75 | 2 |
74 – 63 | 3 |
62 – 50 | 4 |
49 – 0 | 5 |
This seminar builds on proactive participation in the classroom (50 %). The 50 % of the grade is based on students performance in exercises.
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Methods |
This course uses following methods:
- Lectures
- Exercises
- Discussions
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Language |
English |
Study material |
Literature will be assigned in class.
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Changing subject? |
No |
Further information |
Infos and Timeline of the session: see moodle
For quality assurance and improvement purposes, please participate in all
JKU course evaluations and surveys!
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Corresponding lecture |
986CABUMS1S19 MS1: Analytical skills
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On-site course |
Maximum number of participants |
20 |
Assignment procedure |
Direct assignment |
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