Course Information

Course Name	Turkish	Hesaplamalı Veri Bilimi
	English	Computational Data Science
Course Code	MAT 386E	Credit	Lecture (hour/week)	Recitation (hour/week)	Laboratory (hour/week)
Semester	5	3	2	2	-
Course Language		English
Course Coordinator		Burcu Tunga
Course Objectives		1. To teach data warehouse, data extraction, transformation and loading and their applications. 2. To teach mathematical background of data processing algorithms. 3. To apply data processing algorithms to the real life problems. 4. To teach architecture and tools of big data platforms. 5. To teach data analysis and to visualize and to report the results.1. To teach data warehouse, data extraction, transformation and loading and their applications. 2. To teach mathematical background of data processing algorithms. 3. To apply data processing algorithms to the real life problems. 4. To teach architecture and tools of big data platforms. 5. To teach data analysis and to visualize and to report the results.
Course Description		Big Data and project management. Statistical methods and machine learning in data science: Regression analysis and modelling, basic classification and clustering methods. Data warehousing and structure, data extraction, transform and loading (ETL). Performance metrics and risk management. Big data platforms: Architecture (Hadoop, Spark), tools (MapReduce, Spark ML, Kafka, Flink, Hive). Data processing methods. Sectoral applications. Model visualization and evaluation. Data Visualization and reporting and interpretation of results.
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