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Graduate Diploma in Data Science (GD-DATASC) // Attributes, outcomes and skills
You’re currently viewing the 2023 version of this course
About this course
Coordinator
Michael Kirley
Coordinator
Karim Seghouane
Intended learning outcomes
Upon completion of this course, students should be able to:
- Demonstrate basic expertise in statistical modelling and inference, machine learning, and data mining.
- Demonstrate basic expertise in computational methods for machine learning, data mining, expertise in database systems.
- Integrate and apply this expertise to produce solutions for real-world problems using public and private data sources.
- Communicate findings from analyses clearly and effectively, including to an audience with a diverse background in sciences
- Demonstrate skills in the evaluation and synthesis of information from a range of sources and the ability to apply these skills to understand the international peer-reviewed scientific literature and primary research in data science and disciplines relevant to data science;
- Adapt to a rapidly evolving field.
- Demonstrate a fundamental understanding of theoretical underpinnings of algorithms in computer science
- Develop algorithms for scalable software systems using computer networks and/or databases
Generic skills
- Problem-solving skills: the ability to engage with unfamiliar problems and identify relevant solution strategies;
- Analytical skills: the ability to construct and express logical arguments and to work in abstract or general terms to increase the clarity and efficiency of analysis;
- Time management skills: the ability to meet regular deadlines while balancing competing commitments
- Programming and computing skills: the ability to use statistical computing packages and implement algorithms.
Last updated: 26 March 2024