AI310
BIG DATA
- Course Code
- AI310
- Semester
- Sixth Term (Spring)
- Theory+Practice
- 3 + 1
- ECTS
- 4
| Course Type | Compulsory Course |
|---|---|
| Course Level | Bachelor's Degree |
| Year of Study | 3 |
| Semester | Sixth Term (Spring) |
| ECTS | 4 |
| Name of Lecturer(s) | - |
| Learning Outcomes |
At the end of this course, the students; |
| Mode of Delivery | |
| Prerequisites | No |
| Recommended Optional Programme Components | |
| Course Description | This course covers the end-to-end pipeline for large-scale data processing. Topics include data ingestion, data lakes, Hadoop ecosystem, Spark, Kafka, ETL processes, schema design, data wrangling, and orchestration tools (Airflow). Emphasis will be placed on the data workflows used in real-world AI systems. |
| Course Contents | |
| Recommended or Required Reading | * Tom White, "Hadoop: The Definitive Guide", O'Reilly, 4th Edition. * Jules S. Damji et al., "Learning Spark", O'Reilly, 2nd Edition, 2020. * Zhamak Dehghani, "Data Mesh", O'Reilly, 2022. |
| Planned Learning Activities and Teaching Methods | |
| Assessment Methods and Criteria | |
| Language of Instruction | - |
| Work Placement(s) | No |