PHD IN DATA SCIENCE AND ANALYTICS (DSA)
- Data Mining and Knowledge Discovery in Data Science
Sample Elective Courses
- Advanced Database Management for Data Science
- Deep Learning in Data Science
- Foundation of Data Science and Analytics
- Data Science Computing
- Advanced Machine Learning
- Data Analysis and Privacy Protection in Blockchain
- Industrial Analytics
- Data Exploration and Visualization
- Experimental Design and Causal Inference
- Functional Data Analysis
- Spatio-Temporal Data Analysis
- Combination Optimization with Machine Learning
Program Learning Outcomes
01Identify scientific and engineering correlations, significances, and insights in new data science and analytics models, algorithms, tools, principles, frameworks, solutions, and techniques.
02Demonstrate critical thinking and analytical skills from the perspective of data science and analytics.
03Apply a range of qualitative and quantitative research methods for data science and analytics.
04Translate and transform fundamental research insights effectively into data science practice in academic fields and industries.
05Exercise independent thinking and demonstrate effective communication skills in presenting and publishing scientific findings.
06Conduct original research independently and competently showing in-depth knowledge in the field of data science and analytics.
PhD: 21 credits
Normative Program Duration:
Full-time: 3 years (those with a relevant research master’s degree), 4 years (those without a relevant research master’s degree)