Advanced data science unit introduces deep understanding on data exploration, data visualization, statistical analysis, advanced machine learning and deep learning techniques. This unit (NIT3251) allows students to gain hands-on experience with Python, Jupyter Notebooks, and open-ended investigations of real-world practical dataset and novel data science problems. Students will gain better understanding of the characteristics of different algorithms, tools, frameworks, and technologies and know how to solve authentic analytical problems and measure model performance. This unit will enable the students to build portfolio worthy projects and to explore the essential ethical, and social issues in data science.
Unit details
Location:
Study level:
Undergraduate
Credit points:
12
Unit code:
NIT3251
Prerequisites
NIT2151 - Fundamentals of Data Science and
NIT2251 - Machine Learning and Data Mining
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Learning Outcomes
| 1. | Experiment and evaluate various advanced machine learning and deep learning algorithms to analyse real-world problems; | ||
| 2. | Critically reflect on advanced data analytics methods and their importance to support decision making; | ||
| 3. | Conceptualise critical thinking and problem solving on novel data science problems; and | ||
| 4. | Analyse real-world business problems by applying appropriate advanced data science methods and techniques with considerations of data privacy, human factors and professional ethics. |
Assessment
| Assessment type | Description | Grade |
|---|---|---|
| Test | Open book online test | 20% |
| Project | Applied Learning project on real-world problem - code, and report (individual report) | 40% |
| Project | Case study and algorithm implementation - code, and report (group report) | 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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