KdG University of Applied Sciences and Arts
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BELGIUM
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info@kdg.be
Data & A.I. 426383/2327/2324/1/31
Study guide

Data & A.I. 4

26383/2327/2324/1/31
Academic year 2023-24
Is found in:
  • Applied Computer Science (English Programme), programme stage 2
    Specialisation:
    • Artificial Intelligence
This is a single course unit.
Study load: 6 credits
Weight: 6,00
Total study time: 150,00 hours
This course unit is marked out of 20 (rounded to an integer).
Re-sit exam: is possible.
Possibility of deliberation: This course unit is eligible for deliberation according to the criteria as determined by the degree programme you are enrolled in.
Teaching staff: Baekeland Rony, Tawalbeh Saja
Language course: No
Languages: English
Scheduled for: Term 3+4

Study materials - general information: Mandatory

All learning materials can be found on the LMS (Learning Management System) or will be provided by your lecturer.

Teaching methods - general information

This course unit is offered based on the principles Blended Learning. This means that a choice has been made to use a form of education in which digital study material is combined with face-to-face instruction. Face-to-face instruction is based on the preparation by the student.

Teaching methods

Total study time150,00 hours

Learning outcomes

CodeDescription
OLR AIT 1.1The BSc IT professional applies the appropriate analysis and design techniques, recognises patterns and translates a case into functional and non-functional requirements
OLR AIT 1.2The BSc IT professional devises tailor-made solutions for the customer, examines various alternatives and makes a reasoned choice
OLR AIT 2.1The BSc IT professional builds new systems using a robust architecture and applies relevant quality standards and insights.
OLR AIT 2.2The BSc IT professional tests systems or implementations and validates these with the customer
OLR AIT 2.4The BSc IT professional integrates existing and new systems into a coherent whole
OLR AIT 2.6The BSc IT professional collects and processes data and process metrics, stores them and makes them available to retrieve them correctly and efficiently
OLR AIT 4.1The BSc IT professional advises the customer, user, supervisor, and/or manager of the customer.
OLR AIT 6.2The BSc IT professional uses and considers a company's financial and economic aspects and frames them within management decisions and choices

Learning objectives

You know what Business Intelligence (BI) is.
You know different types of BI.
You apply data warehouse design techniques.
You create a data pipeline using ETL to integrate operational system data into a data warehouse.
You know how a good data architecture should look like.
You know the different parts of BI management and can apply certain basic tasks.
You identify Data Governance problems and suggest optimizations.
You identify data quality issues.
You create basic reports.
You create professional and effective data visualisations.
You apply intermediate A.I. techniques to analyse data and make predictions.
You apply intermediate evaluation metrics to the A.I. models to assess robustness.
You change the database content with transaction management and concurrency in mind.
You apply basic adjustments to the logical and physical database structure.
You know different types of NoSQL databases.
You identify which database technology fits best with the given requirements.
You implement a basic NoSQL database.

Subject matter

Business Intelligence introduction
Data analysis techniques: reporting, dashboards, data mining and others
Data visualisation techniques and best practices
BI specific program and project management
Data Governance and data quality
Data Architectures
Data warehouse optimization
Data warehouse design
ETL (Extract, Transform, Load)
Advanced database administration
Different types of NoSQL technologies:
  Document Store
  Columnar databases
  Graph databases
  Search databases
  Key Value databases

Entrance guidance and study counselling

This course integrates course specific guidance. For additional guidance, such as tutoring or mentoring, contact your Study Career counsellor to assess your specific needs.

Assessment - general information

For this course, we combine different types of evaluations.

We can assess you on (a combination of):
• Project assignments
• Skill tests
• Knowledge tests
• Feedback from lecturers, peer students and how you process the feedback

All of these assessments are taken into account. The lecturer(s) will combine all these assessments to check if the student has met all the learning objectives of the course and grades this result.

Details can be found on LMS (learning management system) or will be given by your lecturer.

Assessment

Evaluation(s) for first exam chance
MomentForm%Remark
During the exam period at the end of term 3Job-oriented assignment - with assessment during the exam period0,00This assessment is taken into account for the final result. Check your LMS for the details.
During the exam period at the end of term 3Written closed book exam with laptop0,00This assessment is taken into account for the final result. Check your LMS for the details.
During the exam period at the end of term 4Job-oriented assignment - with assessment during the exam period0,00This assessment is taken into account for the final result. Check your LMS for the details.
During the exam period at the end of term 4Written closed book exam with laptop0,00This assessment is taken into account for the final result. Check your LMS for the details.
During all termscombination of different assessments100,00
Evaluation(s) for re-sit exam
MomentForm%Remark
Re-sit Exam Periodcombination of different assessments100,00
Re-sit Exam PeriodJob-oriented assignment - with assessment during the exam period0,00This assessment is taken into account for the final result. Check your LMS for the details.
Re-sit Exam PeriodWritten closed book exam with laptop0,00This assessment is taken into account for the final result. Check your LMS for the details.

Description Course Sequence

You can add this course unit to your study programme if you obtained a credit for:
- DATA & A.I. 1
- AND for DATA & A.I. 2