Big Data Analytics
Course Syllabus
| Course Code: | ΕΠ13 |
| Semester: | Elective courses – Winter semester |
| ECTS units: | 3 |
| Weekly Teaching Hours: | 3 |
| Course Page: | https://eclass.duth.gr/courses/TME314/ |
| Instructors: | AMANATIADIS AGGELOS |
Course Description
The aim of the course is to provide a broad and practical introduction to programming for the processing and analysis of large datasets (big data) with search, mining and visualization techniques using relational databases, SQL and specialized libraries. It provides an immersion in state-of-the-art tools and techniques for solving contemporary real-world problems (e.g. IoT, Social Nets Computing) involving big data analysis for building applications, predictive models and decision making.
Purpose of the course
The aim of the course is for the student to acquire the skills to:
- Acquire theoretical and practical knowledge of methods and technologies for the representation, extraction, storage and processing of heterogeneous data types in modern algorithmic and programming environments.
- Acquire advanced knowledge and skills in the basic structures, elements and programming idioms of the Python programming language.
Within the course, the skills and programming techniques are applied to a wide range of problems and data sets that cover almost all of the contemporary challenges found in modern manufacturing, economics and business, where decisions are based on large-scale extraction, analysis and processing of unstructured data.
