Block B - Data Understanding and Preparation

Each of the 8 weeks has a fixed structure : on Monday, Wednesday and Thursday you work individually on the development of basic skills, which are needed to execute the DataLab assignments. Kindly follow the table of content below, this will guide you through what is expected of you on a daily basis.

Project Based Learning - Creative Brief

In block A, you explored various themes around digital transformation and critically examined applications of AI and digital technologies to existing businesses processes. In this block, you will take on a more hands-on approach towards improving a business process using digital transformation. In particular, you will explore one specific role within the theme of digitalisation - the data analyst – and help the municipality of Oosterhout improve their business processes using data, mathematics, and machine learning.

One of the key responsibilities of the municipality of Oosterhout (henceforth the client) is youth care. While Dutch children are among the happiest and healthiest in the world, there are still many children that need extra support and care. To ensure a youth care system that is more efficient, coherent and cost-effective, the client has chosen to digitalize their existing youth care process.

The client has approached you – the data analyst – with the aim to discover more efficient (in cost and time) ways of delivering youth care.

At the beginning of the project, you will be introduced to the use-case by a data analyst from one of the municipalities. You can consult the client's data analyst if you have any questions or wish to deepen your understanding of the use-case. Please refer to the project brief for more detailed information.

Creative Brief Requirements:

Please click the links below to view more detailed requirements

Block Outline

Week 1 : Business Intelligence (SQL)

Monday

Data engineering: Data architecture & Pipeline design
SQL: Data Definition Language (DDL) clauses 1 & Data Manipulation Language (DML) clauses
Markdown template (optional)

Tuesday

DataLab: Research design, EDA, and codebook

Wednesday

SQL: Data Query Language (DQL) clauses

Thursday

SQL: Data Definition Language (DDL) clauses 2

Friday

DataLab: Database & SQL assignment

Week 2 : Digital Transformation & Artificial Intelligence

Monday

Ethics & Law (1): Introduction to DEDA Framework. Preparation for debates: Ethical Decision-Making.

Tuesday

DataLab: Debates: Ethical Decision-Making

Wednesday

Ethics & Law (2): Ethical Guidelines for Statistical Practice. Introduction to GDPR.

Thursday

Ethics & Law (3): Preparation for debates: Can AI Systems Be Ethical?

Friday

DataLab: Debates: Can AI Systems Be Ethical?

Week 3 : Business Intelligence (Power BI)

Monday

Getting started with Power BI & Prepare data for analysis with Power BI

Tuesday

DataLab: Data wrangling & UX design in Power BI

Wednesday

Data modeling in Power BI

Thursday

Data visualization in Power BI

Friday

DataLab: Basic visuals & DAX in Power BI

Week 4 : Business Intelligence (Power BI) & Machine Learning

Monday

Data analysis & Managing workspaces/datasets in Power BI

Tuesday

DataLab: Advanced visuals & Analyzing data in Power BI

Wednesday

Supervised and Unsupervised Learning

Thursday

Regression Algorithms

Friday

DataLab: Regression Algorithms

Week 5 : Machine Learning and Mathematics

Monday

Introduction to Linear Algebra

Tuesday

DataLab: Implementing elementary operations on matrices using Python

Wednesday

Linear algebra applied to Linear Systems

Thursday

Classifications Algorithms

Friday

DAY OFF: CHRISTMAS HOLIDAYS! :D

Week 6 : Machine Learning and Mathematics

Monday

Linear Algebra and Linear models (least squares)

Tuesday

Because of the online teaching situation, we're forced to change our schedule around a bit. Datalab will still follow it's normal structure but we're going to use this Datalab day to make sure we have week 4 and 5 properly covered. Therefore, after the Q&A, we do our week 5 Math Datalab day and in the afternoon we will finish week 4's machine learning Datalab day for those who haven't finished it yet. Furthermore, from 10:00 till 16:00 we will have some brief one-on-one meetings to check everyone's progress where we'll ask you to show your learning log and project progress thus far. The schedule will therefore be as follows:

Schedule

9:00 – 9:30 Stand-up in breakout rooms
9:30 – 10:00 Q&A
10:00 – 12:30 DataLab: Implementing elementary operations on matrices using Python
12:30 – 13:30 Lunch
13:30 – 16:00 DataLab: Regression Algorithms; continue where you left off last time!
16:00 – 16:30 Day evaluation
16:30 – 17:00 Fill in your Work- & Learning log