CENG790 BIG DATA ANALYTICS
| Course Code: | 5710790 |
| METU Credit (Theoretical-Laboratory hours/week): | 3 (3.00 - 0.00) |
| ECTS Credit: | 8.0 |
| Department: | Computer Engineering |
| Language of Instruction: | English |
| Level of Study: | Graduate |
| Course Coordinator: | Assoc.Prof.Dr. HANDE ALEMDAR |
| Offered Semester: | Fall and Spring Semesters. |
Course Objectives
At the end of this course the students will be able to:
- Define big data and its features, and identify what are and are not big data problems.
- Describe the data storage and retrieval requirements for big data and utilize common big data platforms (Apache Hadoop and Spark) for storage of and retrieval on large-scale databases.
- Identify and apply appropriate machine learning algorithms for big data analytics tasks.
- Apply real-time analytics on big data streams.
- Model a problem into a graph database and perform analytics in a scalable manner.
Course Content
Introduction to big data, big data platforms; storage and retrieval architectures for large-sale data; machine learning algorithms and tools for big data analytics; data stream features and real-time analytics on data streams; graph representation of linked big data; large-scale graph analytics algorithms and tools.