Programming for Data Science G (11521.2)

Beyond the foundational knowledge of using R for data science, data scientists need to be proficient in valuable programming tools and languages that form the basis of advanced analysis and modelling techniques. Using real-world data sets and a problem-solving framework, students in this unit will learn industry-standard programming skills and best practises for data organisation, data manipulation, data interrogation and data modelling relevant to data science. Students will develop a sound understanding of technical programming in one or more languages and related computational modelling and analysis tools. This includes skills in software engineering, such as writing correct code, working with version control tools, testing and debugging. A particular emphasis will be on tackling real-world data science problems as found in industry.

Learning outcomes

After successful completion of this unit, students will be able to:
1. Analyse and apply fundamentals of programming in Python and/or other relevant languages utilising common libraries and tools to implement software solutions;
2. Apply software engineering best practices, including code development, large database integration, testing and debugging, and version control to create industry-aligned software;
3. Critically reflect on available computational tools for solving data science problems;
4. Successfully demonstrate practical skills in developing solutions to data science problems.

Graduate attributes

1. UC graduates are professional - employ up-to-date and relevant knowledge and skills
1. UC graduates are professional - use creativity, critical thinking, analysis and research skills to solve theoretical and real-world problems
2. UC graduates are global citizens - make creative use of technology in their learning and professional lives
3. UC graduates are lifelong learners - reflect on their own practice, updating and adapting their knowledge and skills for continual professional and academic development
2. UC graduates are global citizens - think globally about issues in their profession
2. UC graduates are global citizens - adopt an informed and balanced approach across professional and international boundaries
3. UC graduates are lifelong learners - evaluate and adopt new technology
1. UC graduates are professional - work collaboratively as part of a team, negotiate, and resolve conflict
1. UC graduates are professional - display initiative and drive, and use their organisation skills to plan and manage their workload
1. UC graduates are professional - take pride in their professional and personal integrity
2. UC graduates are global citizens - communicate effectively in diverse cultural and social settings
2. UC graduates are global citizens - behave ethically and sustainably in their professional and personal lives
3. UC graduates are lifelong learners - adapt to complexity, ambiguity and change by being flexible and keen to engage with new ideas

Prerequisites

11516 Introduction to Data Science G

Corequisites

None.

Incompatible units

None.

Equivalent units

None.

Assumed knowledge

Working knowledge of discrete mathematics, algebra and numerical analysis.