| Code | Name of the Course Unit | Semester | In-Class Hours (T+P) | Credit | ECTS Credit |
|---|---|---|---|---|---|
| YBS413 | BIG DATA ANALYSIS | 7 | 3 | 3 | 8 |
Objectives and Contents |
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|---|---|
| Objectives: | This course aims to provide the students with the basic knowledge that will enable them to handle the difficulties. The Big Data field has many disciplines by its very nature. As it becomes popular, many software and hardware tools and new algorithms emerge. A data scientist must follow these changing trends to deal with real-world challenges. |
| Content: | Contents of the course include the subjects such as basic platforms such as Hadoop, Spark, and tools like IBM System G for big data, large scale machine learning methods, which are the basis for artificial intelligence and cognitive networks, Intel and Power chips, analytical optimization methods for different hardware platforms such as GPU and FPGA, difficulties in Linked Big Data field including issues such as graph, graphical models, spatial-temporal analysis, cognitive analytics etc. |