People are saying, 'Big Data is the new oil.'
HDip Schedule (Full-Time)
HOW THIS PROGRAMME IS STRUCTURED
You are reading the full-time schedule for this programme, here is the part-time schedule which applies to the evening delivery of the programme.
The HDip in Data Science and Analytics programme is delivered over two semesters, each semester has a 13 week teaching block. Taught semesters normally have modules with a value of 5 ECTS credits giving 30 ECTS credits per semester and 60 ECTS credits per year. The tables below list the modules in each semester of the progrmme and contain hyperlinks to module descriptors. Each module descriptor contains detailed information such as learning outcomes, indicative content and assessment methods, for example.
Students select one elective in the second semester and only the most popular elective will be subsequently scheduled. The number of electives offered depends on the number of students in an elective class. Electives with small student numbers will not be offered.
Semester 1
| Module | Mandatory/Elective | ECTS Credits |
|---|---|---|
| DATA8001 - Data Science and Analytics | Mandatory | 5 |
| DATA8002 - Data Management Systems | Mandatory | 5 |
| COMP8060 - Scientific Prog in Python | Mandatory | 5 |
| STAT8006 - Applied Stats & Probability | Mandatory | 5 |
| STAT8010 - Intro to R for Data Science | Mandatory | 5 |
| MATH8009 - Maths Methods and Modelling | Mandatory | 5 |
Semester 2
| Module | Mandatory/Elective | ECTS Credits |
|---|---|---|
| STAT8011 - Regression Analysis | Mandatory | 5 |
| DATA8005 - Distributed Data Management | Mandatory | 5 |
| DATA8008 - Data Visualisation & Analytics | Mandatory | 5 |
| DATA8006 - Data Science Analytics Project | Mandatory | 10 |
| STAT8008 - Time Series & PCA | Elective | 5 |
| COMP8043 - Machine Learning | Elective | 5 |
