Applied Programming for Data Science
Course code
ULP6613-25230
old course code
Course title in Estonian
Rakenduslik programmeerimine andmeteaduses
Course title in English
Applied Programming for Data Science
ECTS credits
6.0
Assessment form
Examination
lecturer of 2023/2024 Spring semester
Not opened for teaching. Click the study programme link below to see the nominal division schedule.
lecturer of 2024/2025 Autumn semester
Not opened for teaching. Click the study programme link below to see the nominal division schedule.
Course aims
The course aims to deliver an insight on the problems related to handling big volumes of data, covering statistical comprehension, data storage and data processing. The course covers theoretical formulation of the algorithms, aiming for a better analysis of the outcomes of the proposed strategies.
Brief description of the course
The course is focuses on problems with large-scale data mining, computational architectures and setting Python software environments. Furthermore, it addresses the MapReduce, Hadoop, statistical data analysis and data storage, relational vs non-relational databases, MongoDB.
Learning outcomes in the course
Upon completing the course the student:
- knows different strategies and algorithms for data science;
- is capable of using tools and proper computational frameworks that enable big data processing;
- knows how to develop advanced specific knowledge and skills on programming languages for data science and its associated libraries or modules, e.g. Python.
- knows different strategies and algorithms for data science;
- is capable of using tools and proper computational frameworks that enable big data processing;
- knows how to develop advanced specific knowledge and skills on programming languages for data science and its associated libraries or modules, e.g. Python.
Teacher
João Pedro Leal Abalada De Matos Carvalho
Study programmes containing that course