Graduate Diploma in Foundational Data Science (GD-FDATASC) // Attributes, outcomes and skills

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.