Study Guide

Learning outcomes

The student is able to
- understand RPA and AI concepts, and its value proposition
- is able to identify potential automation examples and draw up a plan for an implementation
- use RPA and AI tools

Implementation and methods of teaching

The AIna robot acts as your guide and introduces you to the different areas of front and back office process development.

The aim of the course is to increase digital competence, especially from the point of view of process efficiency. You will find answers e.g. to the following questions: What is process-oriented thinking? What is digital data? What is process mining used for? What are the different forms of artificial intelligence? How to automate repetitive tasks on a computer? After completing the course, you will be able to recognize the possibilities of office automation in your own operations and you will find areas of development where automation can achieve the best benefit.

About the course in brief:
- Scope 5 credits
- Learning takes place in small parts (micro learning)
- You can study flexibly regardless of time and place
- You can learn basic information on mobile, for practical exercises you need a computer
- You will receive a diploma and a badge for completing the course

Timing and attendance

The course is 100% online. The course is a HopOn course. The course is open from 8 January 2024 to 31 December 2024.

Learning material and recommended literature

All course learning material is available in the course's MOOC learning environment.

Alternative completion methods

The course can only be completed as described.

Working life cooperation

The course has been developed together with working life. In the course, you will learn modern methods and use the latest tools of working life.

Tools and systems used in the course: Microsoft PowerPoint, Excel and Notepad, ARIS Process Mining, UiPath Studio, Task Capture and Task Mining, ChatGPT, DALL-E-2, Microsoft Power Platform: Power Automate, Task Mining, Process Mining, AI Builder, Power BI.

Learning environment

Note! UiPath Studio, UiPath Task Capture, UiPath Task Mining Recorder, Microsoft Power BI desktop and Microsoft Process Mining desktop app can be installed only on Windows environment. You must therefore have a Windows machine to complete the course. If you are a LAB student and have a Mac computer, you can use the UiPath programs on a LAB Win10 2D virtual workstation (LAB account required). Please take this into account before starting the course.

Student time use and work load

The scope of the course is 5 ECTS credits. In terms of workload, the course corresponds to 135 hours, or about 3.5 weeks of full-time work.

Contents

In this practical 'hands-on' course, you will learn to model and develop office and information work processes. In the course, basic information is learned using micro-learning methods (also possible on mobile), for practical exercises you need a computer.

Learning is divided into five sections, which are displayed on their own tabs:

1. Process development: You will learn to model, analyze and optimize the work phases of information work.

2. Data and process mining: You will learn the basics of digital data and the data economy. In addition, you will learn how to measure and analyze log data using process mining methods.

3. Artificial intelligence (AI): You will learn what artificial intelligence means and what it can be used for. You will learn to make your own artificial intelligence applications.

4. Robotic process automation (RPA): You will learn how to automate the repetitive tasks of office work.

5. Hyperautomation: You will learn how RPA and AI can be combined.

Additional information for students: previous knowledge etc.

No previous studies are required.

Assessment criteria

The course will be graded as failed or approved.

Assessment scale

Approved/Failed

Assessment criteria: assessment scale failed/approved

The course completion is approved when you have

- completed all tasks and exercises with approval. The pass threshold for assessed assignments is 50%.
- completed the section exams passably. The passing threshold for exams is 50%.