| Author: | Hans Bouwknegt, Abhishek Biswas, Frank Peters |
| Learning Line: | DataLab |
| Course: | DataLab 1 |
| Week: | 1 |
| Competencies: | 2, 4, 5, 6, 7, 8, 9, 10, 11, 12 |
| BoKS: | 1K1, Project Management: Knows how to plan, control, budget and assess the risk of an AI & Data Science project. 1K4, Knows how to report and present AI & Data Science projects. 1S1, (Agile) project management: Is able to plan, control, budget and assess the risk of an AI & Data Science project. 1S2, Is able to communicate AI & Data Science projects, in written (document), oral (presentation) and hybrid form (poster presentation). 1S4, Is able to integrate various AI & Data Science expertise areas in a project. 4K1, Knows user-centered design principles and processes. A2, Learning as a basic attitude, self-development. A4, Resilient in challenges. A5, Collaborative. A8, Self-reflective. A9, Pro-active. A11, Investigative: be genuinely interested in learning and find critical aspects for their further improvement. |
| Learning Goals: | Within the requirements of a basic project, in agiven environment and under guidance, the student will: Content (Focus on Data Science): – The student understands how to approach challenges data-analytically, using the data-mining process to gather good data in the most appropriate way – The student understands the general concepts for extracting knowledge from data and knows how to apply them on basic data sets – The student had a basic understanding of how data science can help organizations solving problems Process: – The student is able to distinguish the different phases of a data science project and know how to apply parts of those phases – The student knows how to integrate one expertise area -data science- in an AI or data science project The student is able to set up a solid argument, which is supported by data insights. |
Content
Data science projects have a common approach which is displayed below in figure 1. This scheme serves the standard approach to all the projects you are going to do in the next four years. You’ll be taught to use knowledge on Data Science, Artificial Intelligence, digital transformation processes and programming to solve various practical problems, using the standard approach displayed below in figure 1.
In order to clarify this approach, the video below is placed here. Watch it, not focussing on the details (we don’t educate astrologists), but on the approach. You can fast forward the video where it becomes too detailled.
In order to be able to do the current project, you need to know the concept of rectangular datasets:
Process approach
Traditionally, projects were planned in detail upfront. Modern approaches of project management are more flexible. We call them Agile methodologies. Watch the video below to understand how this works:
An example of agile project management which is used in the AAI&DM programme is Scrum, a methodology explained below:
Software we use to facilitate agile project management is Jira, which is explained below.
Assignments
Install Jupyter Notebook , Python via Anaconda on windows. An instruction can be found here:
Working with Jupyter Notebook:
Course on Jupyter notebook (free if you login through BUas portal):