- Code COMP6420
- Unit Value 6 units
- Offered by Research School of Computer Science
- ANU College ANU College of Engineering and Computer Science
- Course subject Computer Science
- Academic career PGRD
- Dr Ramesh Sankaranarayana
- Mode of delivery In Person
- Co-taught Course
First Semester 2019
See Future Offerings
Commerce and research are being transformed by data-driven discovery and prediction. Skills required for data analytics at massive levels - scalable data management on and off the cloud, parallel algorithms, statistical modeling, and proficiency with a complex ecosystem of tools and platforms - span a variety of disciplines and are not easy to obtain through conventional curricula. Tour the basic techniques of data science, including both SQL and NoSQL solutions for massive data management, basic statistical modeling (e.g., descriptive statistics, linear and non-linear regression), algorithms for machine learning and optimization, and fundamentals of knowledge representation and search. Learn key concepts in security and the use of cryptographic techniques in securing data.
Upon successful completion, students will have the knowledge and skills to:
- Demonstrate a conceptual understanding of database systems and architecture, data models and declarative query languages
- Define, query and manipulate a relational database
- Demonstrate basic knowledge and understanding of descriptive and predictive data analysis methods, optimization and search, and knowledge representation.
- Formulate and extract descriptive and predictive statistics from data
- Analyse and interpret results from descriptive and predictive data analysis
- Apply their knowledge to a given problem domain and articulate potential data analysis problems
- Identify potential pitfalls, and social and ethical implications of data science
- Explain key security concepts and the use of cryptographic techniques, digital signatures and PKI in security
- Assignments (30) [LO null]
- Labs (5) [LO null]
- Mid-semester exam (15) [LO null]
- Final exam (50) [LO null]
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WorkloadUp to 36 one-hour lectures and eight two-hour labs.
Requisite and Incompatibility
Tuition fees are for the academic year indicated at the top of the page.
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- Student Contribution Band:
- Unit value:
- 6 units
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Offerings, Dates and Class Summary Links
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Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
|Class number||Class start date||Last day to enrol||Census date||Class end date||Mode Of Delivery||Class Summary|
|4119||25 Feb 2019||04 Mar 2019||31 Mar 2019||31 May 2019||In Person||N/A|