COURSE UNIT TITLE

Offered By

Economics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR FIRAT GÜNDEM

Offered to

Economics (Evening)
Economics

Course Objective

The course on Introduction to Data Science for Economists provides an overview of Data Science, covering a broad selection of key challenges and methodologies for working with big data. Topics to be covered include data collection, integration, management, modeling, analysis, visualization, prediction, and informed decision making from the economics point of view. This introductory course is integrative across the core disciplines of Data Science, including databases, data warehousing, statistics, data mining, data visualization, high-performance computing, computational social sciences, and economics. Professional skills, such as communication, presentation, and storytelling with data, will be fostered. Students will acquire a working knowledge of data science through homework and case studies in a variety of social sciences, economics, and life sciences domains.

Learning Outcomes of the Course Unit

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Recomended or Required Reading

James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning (Vol. 112, p. 18). New York: springer.

Taddy, M. (2019). Business data science: Combining machine learning and economics to optimize, automate, and accelerate business decisions. McGraw Hill Professional.

Arslan, I. (2019). Python ile Veri Bilimi. Pusula.

Gursakal, N. (2021). Makine Ogrenmesi. Dora Yayincilik

https://boun101.boun.edu.tr/classes/veri-bilimine-giris/

Planned Learning Activities and Teaching Methods

Assessment Methods

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Contribution of Learning Outcomes to Programme Outcomes