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

Study level:
Credit points:
Unit code:


NIT2151 - Fundamentals of Data Science and

NIT2251 - Machine Learning and Data Mining

Learning Outcomes

On successful completion of this unit, students will be able to:
  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 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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