Machine learning and reasoning with built environment data (5 ECTS)

Objective

The student can identify and explain the basic concepts of validating data and deriving new data from existing data through data analysis, machine learning, machine inference, rule-based systems, and artificial intelligence in general. The student understands the benefits and prerequisites of the technologies and the potential use scenarios in construction domain. The student knows and can apply a set of tools for data validation and data derivation for data in construction domain. The student can programmatically integrate these technologies to broader software solutions in the construction domain.

Content

- Introduction to artificial intelligence, learning and reasoning
- Application areas of artificial intelligence technologies in the construction domain
- Machine learning approaches, including neural networks and deep learning
- Semantic models
- Logical and ontology-based reasoning
- Knowledge graphs in construction
- Rule-based reasoning and validation
- Rule-based checking of BIM models

Evaluation scale

0-5

Assessment criteria, satisfactory (1)

The student has achieved the minimal objectives of the course. The student can identify and explain the concepts and approaches related to data analysis, machine learning, reasoning, and rule-based systems and their potential use scenarios in the construction domain. The student knows and is familiar with some software tools in the area. The student has completed the required learning exercises in minimum requirement level. The competencies acquired form the basis for the student to build his/her knowledge in machine learning and reasoning in construction domain, eventually enabling a job position in applying these tools.

Assessment criteria, good (3)

The student has achieved the objectives of the course well, even though the knowledge and skills need improvement on some areas. The student can identify and explain the concepts and approaches related to data analysis, machine learning, reasoning, and rule-based systems and their potential use scenarios in the construction domain. The student knows and can apply software tools in the area. The student has completed the required learning exercises in good or satisfactory level. The student is able to create software solutions incorporating machine learning and reasoning functionalities. The student has the capability to apply the knowledge in further studies and in software development work related machine learning and reasoning.

Assessment criteria, excellent (5)

The student has achieved the objectives of the course with excellence. The student can identify and explain the concepts and approaches related to data analysis, machine learning, reasoning, and rule-based systems and their potential use scenarios in the construction domain. The student knows and can apply multiple software tools in the area. The student has completed the required learning exercises in excellent or good level. The student is able to integrate well-placed machine learning and reasoning functionalities in complex software solutions in a justified manner. The student has an excellent basis to apply the knowledge in further studies and in software development related to machine learning and reasoning.

Qualifications

TX00FE95
TX00FE96