Data Science Applications microcredential

The ‘Data Science Principles’ (DSP) subject is taught as part of the Actuary Program. This syllabus covers:

• Business understanding
• Data understanding and preparation
• Modelling
• Evaluation
• Communication

The full subject syllabus has details about learning objectives for each of these topics.

Some of the more technical learning objectives of the DSP syllabus are covered in:

• Textbooks such as: James, G., Witten, D., Hastie, T., and Tibshirani, R. (2017). An Introduction to Statistical Learning with Applications in R, Springer, https://www.statlearning.com/ ; and
• Online courses such as: Stanford University. Machine Learning. [Online course]. Coursera. https://www.coursera.org/browse

Students intending to undertake the assessments should have a basic understanding of Python prior to undertaking the Data Science Applications microcredential. This basic understanding should cover topics such as: 


• data types 

• storing values in variables

• using standard functions (e.g. print(), input())

• basic error handling (e.g. try and except statements)

• boolean and comparison operators

• flow control statements (e.g. ‘if, elif, else’, while and for loops)

• importing and working with modules/libraries (e.g. numpy and pandas)

• writing functions

• working with lists

• working with dictionaries

• manipulating strings

• reading and writing datasets

• manipulating datasets

Examples of resources that cover many of these topics are:

• textbooks such as: Sweigart, A. (2020). Automate the boring stuff with Python: Practical programming for total beginners. https://automatetheboringstuff.com/ ; and
• online courses such as: Data Camp’s Introduction to Python and Intermediate Python

Students who undertake the Data Science Applications microcredential will be provided with Python-based practice exercises, case studies and solutions to further develop their Python coding skills.

Students will also have access to a discussion board and tutorials where the Chief Examiner and fellow students will help them solve issues they encounter when coding in Python. They will also learn how to problem-solve using web sites such as Stack Overflow.

Google Colab is a requirement for this subject. If you are unable to access Colab you may utilise an equivalent solution, with prior approval from the Institute. For example, there may be difficulties in China due to firewall restrictions. 



To apply for the use of alternative software, please complete and submit our Application for Alternative Software Use — DSA.