This module intends to provide crucial supplementary knowledge, skills, and competencies to design, develop, and execute data science projects in business and research settings. This includes the acquisition, processing, and storage of typical real-world data within big data frameworks. Prospect students will learn how to query databases via an application programming interface (API), and how to work within common database frameworks suitable for structured, unstructured, dynamic, and big data. In addition, prospect students will learn how to refracture machine learning models and the necessary code and deploy it in web-based applications.
Insights and techniques learned in this module can be applied to real-world problems related to the deployment of machine learning models in end-to-end solutions, encompassing all steps from data acquisition to the application of machine learning models in production and service workflows.
Upon completion of the module students will have built a solid knowledge on processes, techniques, and workflows to provide functioning machine learning solutions in a real-world setting. Students will be capable of autonomously planning, managing, and executing complex machine learning projects, and provide client-facing application interfaces thereof.
The objective is that the student after the module possesses the necessary knowledge on:
The objective is that the student after the module possesses the necessary skills in:
The objective is that the student after the module possesses the necessary competences in:
For information see § 17.
|Name of exam
|Data Engineering and Machine Learning Operations in Business
|Type of exam
Oral exam based on a projectGroup examination with max. 5 students.
|7-point grading scale
|Type of grading
|Criteria of assessment
|The criteria of assessment are stated in the Examination Policies and Procedures
|Datateknik og ML operationer og maskinlæring i virksomheder
|Language of instruction
|Location of the lecture
|Responsible for the module
|Study Board of Economics and Business Administration
|Aalborg University Business School
|Faculty of Social Sciences and Humanities