| Code | DE0749 | ||||||||||||||||||||||||||||||||||||||||||||
| Name | Advanced Analytics and Knowledge Technologies | ||||||||||||||||||||||||||||||||||||||||||||
| Status | Compulsory/Courses of Limited Choice | ||||||||||||||||||||||||||||||||||||||||||||
| Level and type | Post-graduate Studies, Academic | ||||||||||||||||||||||||||||||||||||||||||||
| Field of study | Computer Science | ||||||||||||||||||||||||||||||||||||||||||||
| Faculty | |||||||||||||||||||||||||||||||||||||||||||||
| Academic staff | Ilze Birzniece, Mārīte Kirikova, Māra Romanovska | ||||||||||||||||||||||||||||||||||||||||||||
| Credit points | 6.0 | ||||||||||||||||||||||||||||||||||||||||||||
| Parts | 1 | ||||||||||||||||||||||||||||||||||||||||||||
| Annotation |
Advanced analytics and knowledge technologies nowadays play a key role in dealing with varied forms of information, structured and unstructured, at the intersection of people, processes and technology in order to create value for the organization. In the study course, students will learn about knowledge management in enterprises and understand the challenges related to processing different data types. The study course will provide insight into appropriate analytical methods and tools to be deployed to create, extract, maintain, renew and propagate business knowledge in order to capitalise from the information assets.. |
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| Contents |
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Goals and objectives of the course in terms of competences and skills |
The goal of the study course is to provide the knowledge of capabilities from data analytics and knowledge management in enterprises as well as skills to extract the knowledge from data. The objectives of the study course are: 1. to develop competencies for identifying, extracting, and managing data and knowledge within organizations; 2. to acquaint with analytics for different kinds of data and tasks; 3. to provide skills in selecting and applying methods of advanced analytics and other knowledge technologies; 4. to improve an understanding of the role of these technologies in organizational knowledge management. | ||||||||||||||||||||||||||||||||||||||||||||
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Learning outcomes and assessment |
Understands the role of knowledge management in enterprises. - Individual assignment ((students' presentations on the most important factors of knowledge management). Understands commonalities and differences in human and artificial knowledge. - Individual assignment (students' presentations on the most important common and different features of natural and artificial knowledge). Is able to describe the main analytical approaches and recommend appropriate solutions, linking the possibilities and needs of the problem area with the available analytical solutions. - Practical works, project (group assignment), examination. Is able to apply data mining and knowledge representation tools and select methods that allow supporting data properties and business needs. - Practical works, project (group assignment), examination. Understands the challenges and opportunities of Big Data, Linked and Open Data. - Examination. Is able to integrate classical knowledge management methods and advanced knowledge technologies. - Individual assignment (homework). Orients in technologies of advanced analytics and their capabilities in varied applications. - Individual assignment (students' presentation), examination. Is able to perform different tasks according to the principles of academic integrity and ethics in research and business. - Individual assignments, practical works, project (group assignment), examination. |
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| Evaluation criteria of study results |
Individual assignments (presentations, homework) - 15%
Practical works - 25% Project - 30% Examination - 30% |
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| Course prerequisites | Knowledge in databases and basics of artificial intelligence. | ||||||||||||||||||||||||||||||||||||||||||||
| Course planning |
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