Fundamentals of Data Science is a unit designed to introduce the students to fundamental data science techniques, including discrete mathematics, statistical analysis, data visualisation, data structures and algorithms using a high-level programming language. This unit (NIT2151) will also take students through the fundamental processes of data analysis for business use including requirement analysis, data manipulation, data preparation, model evaluation, and basic data mining for future predictions. Ethical considerations, policies, and legislations for data science will be introduced. The unit will provide hands-on experience with case studies to basic data analysis methods and programming paradigms.
Unit details
Location:
Study level:
Undergraduate
Credit points:
12
Unit code:
NIT2151
Prerequisites
NIT1102 - Introduction to Programming
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Learning Outcomes
1. | Discuss review the functions of and solve problems related to data administration in organisations; | ||
2. | Apply fundamental theoretical foundations and basic mathematics for exploratory data analysis and visualisation; | ||
3. | Manipulate contemporary data analytics and its use in real-world scenarios; | ||
4. | Apply fundamental techniques to collect and process big data; and | ||
5. | Discuss data security and privacy regulations and ethical constrains. |
Assessment
Assessment type | Description | Grade |
---|---|---|
Test | Open book online test (fundamental programming knowledge and basic discrete mathematics skills) | 20% |
Project | Group Project based assessment (comprehensive data analysis process with given business case study) | 40% |
Case Study | Scenario-based in-class problem solving (Individual assessment with given scenarios and answer questions by the knowledge acquired from learning) | 40% |
Where to next?
As part of a course
This unit is studied as part of the following courses. Refer to the course page for information on how to apply for the course.
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