BSc - Data Analytics as a major
Major
If you're intrigued by the natural world around you, or enjoy understanding how things work, Waikato's Bachelor of Science (BSc) is what you're looking for. Putting into practice what you learn in your lectures is a major part of this degree. You will gain hands-on experience with some of the most up-to-date and high-tech computing facilities and laboratory equipment.
Enhance productivity and help make more informed decisions, while using your Computer Science and Statistical analysis skills, through Data Analytics.
Apply to enrol
Key information
| Years: | 3 |
|---|---|
| Points: | 360 |
| Start Dates: | Trimester A (March) and Trimester B (July) |
| Estimated Fees* (Domestic): | $7,821 per year |
| Estimated Fees* (International): | $36,830 - $38,305 per year |
| Entry Requirements: | Undergraduate International |
| Area of Study: | |
| All amounts are in New Zealand Dollars (NZD). *Tuition fees shown are indicative only and may change. There are additional fees and charges related to enrolment please see the Table of Fees and Charges for more information. You will be sent an enrolment agreement which will confirm your fees. | |
Career opportunities
- Biometrics
- Business Analyst
- Data Analyst
- Government Statistician
- Industrial Statistician
- Insurance and Finance
- Market Researcher
- Medical Statistician
- Operational Researcher
Degree Planner
Degree planner — BSc in Data Analytics
If no point value is listed, papers are worth 15 points. This structure applies to study starting in 2021.
Year 1
One of
DATAX111 or DATAX121
One of
COMPX101 or ENGEN103
100 level
Science paper
100 level
Science paper
Elective
Elective
Year 2
200 level
Science paper
Elective
Elective
Elective
Year 3
300 level
Data Analytics paper
300 level
Data Analytics paper
300 level
Data Analytics paper
One from List A:
Work-Integrated Learning
Elective
Elective
Elective
- Major
- Compulsory
- Elective
Data Analytics papers
Papers
Papers available within Data Analytics
Data Analytics is the science of collecting and interpreting data subject to uncertainty. We live in a world where variability is everywhere. To make informed decisions we must understand the nature of variability, and make use of meaningful information. Without data we have to resort to hunches or guesses, neither of which can be relied on. Data Analytics tells us how to deal with variability, and how to collect and use data so that we can make good decisions.
Data Analytics is available as a specified programme for the Bachelor of Computer Science (BCompSc) - see the Prescriptions for the BCompSc.
Data Analytics is available as a first major for the Bachelor of Climate Change (BCC), Bachelor of Computing and Mathematical Sciences with Honours (BCMS(Hons)) and the Bachelor of Science (BSc). Data Analytics may also be taken as a second major or minor, subject to approval of the Division in which the student is enrolled.
To complete Data Analytics as a single major for the BCC, BCMS(Hons) or the BSc, students must gain 135 points from papers listed for Data Analytics, including 105 points above 100 level, and 60 points above 200 level. Students must complete COMPX101 or ENGEN103, DATAX111 or DATAX121, COMPX223, DATAX221, DATAX222, and DATAX321. Students in the BCMS(Hons) will also need to take at least 60 points in the subject of Data Analytics at 500 level, including DATAX520.
To complete Data Analytics as part of a double major for the BCC, BCMS(Hons), BSc or other undergraduate degree, students must gain 120 points from papers listed for Data Analytics, including 90 points above 100 level, and 45 points above 200 level. Students must complete COMPX101 or ENGEN103, DATAX111 or DATAX121, COMPX223, DATAX221, DATAX222, and DATAX321. Students in the BCMS(Hons) will also need to take at least 60 points in the subject of their first major at 500 level, including DATAX520 if Data Analytics is the first major.
To complete a minor in Data Analytics, students must complete 60 points from the papers listed for the Data Analytics major, including at least 30 points at 200 level or above consisting of at least one DATAX-coded paper and at least one COMPX-coded paper.
100 Level
| Code | Paper Title | Points | Occurrence / Location |
|---|---|---|---|
| COMPX101 | Introduction to Programming | 15.0 | 24A (Hamilton), 24A (Online), 24B (Hamilton), 24B (Hamilton Waikato College), 24B (Secondary School - Unistart), 24X (Hainan University, Haikou, China) & 24X (Zhejiang University City College, Hangzhou China) |
| This paper introduces computer programming in C# - the exciting challenge of creating software and designing artificial worlds within the computer. It also covers concepts such as the internals of the home computer, the history and future of computers, cyber security, computer gaming, databases, mobile computing and current researc... | |||
| CSMAX170 | Foundations in Computing and Mathematical Sciences | 15.0 | 24A (Hamilton), 24A (Tauranga), 24X (Hainan University, Haikou, China) & 24X (Hamilton Waikato College) |
| The objective of this paper is to provide students with the academic foundations for computing and mathematical sciences. The paper will cover the following areas: -Effective academic reasoning and communication -Information literacy and research skills -Academic integrity -Techniques and tools in the computing and mathematical sci... | |||
| DATAX111 | Statistics for Science | 15.0 | 24B (Hamilton), 24B (Tauranga) & 24C (Hamilton Waikato College) |
| An introductory paper in statistics that uses Microsoft Excel. Topics include the collection and presentation of data, basic principles of experimental design, hypothesis testing, regression and the analysis of categorical data. | |||
| DATAX121 | Introduction to Statistical Methods | 15.0 | 24A (Hamilton), 24A (Secondary School - Unistart) & 24X (Hainan University, Haikou, China) |
| An introduction to statistical data collection and analysis. Topics include general principles for statistical problem solving; some practical examples of statistical inference; and the study of relationships between variables using regression analysis. | |||
| ENGEN103 | Engineering Computing | 15.0 | 24A (Hamilton), 24A (Tauranga), 24G (Hamilton) & 24X (Hainan University, Haikou, China) |
| This paper introduces computer programming in languages such as the MATLAB and Python languages. It provides the basis for the programming skills required in more advanced papers. | |||
200 Level
| Code | Paper Title | Points | Occurrence / Location |
|---|---|---|---|
| COMPX223 | Database Practice and Experience | 15.0 | 24A (Hamilton), 24A (Secondary School - Unistart) & 24A (Tauranga) |
| This paper approaches the subject of databases from a practical perspective - how do I create a database and how do I retrieve/update data. Both aspects are heavily addressed in this paper. Database creation and querying, using SQL, will be introduced in lectures as you will master practical skills associated with a commercial Data... | |||
| CSMAX270 | Cultural Perspectives for Computing and Mathematical Sciences | 15.0 | 24B (Hamilton) & 24B (Tauranga) |
| The paper provides students with an understanding of scientific and culture-specific perspectives on issues in computing and mathematical sciences. Students will learn how these perspectives can be applied in diverse cultural, international, ethical, and professional contexts. | |||
| DATAX201 | Practical Data Science | 15.0 | 24B (Hamilton), 24B (Online) & 24B (Tauranga) |
| This paper gives students practical experience for the entire data science process. It covers the data collection process, data cleaning and manipulation, and data visualisation and presentation. | |||
| DATAX221 | Statistical Data Analysis | 15.0 | 24A (Hamilton) |
| This paper introduces students to the R programming language which is used to investigate a collection of real data sets. Analysis of variance, multiple regression, non parametric methods and time series are covered. | |||
| DATAX222 | Principles of Probability and Statistics | 15.0 | 24B (Hamilton) |
| This paper introduces the theoretical background that underpins modern probability and statistics. Topics include discrete probability and mathematical statistics from a frequentist and Bayesian viewpoint. | |||
300 Level
| Code | Paper Title | Points | Occurrence / Location |
|---|---|---|---|
| COMPX310 | Machine Learning | 15.0 | 24B (Hamilton) & 24B (Tauranga) |
| This paper introduces Machine Learning (ML) which is the science of making predictions. ML algorithms strive to be fast and highly accurate, while processing large datasets. This paper will use standard Python-based ML toolkits to teach the fundamentals of ML. | |||
| CSMAX300 | Visual Data Communication | 15.0 | 24A (Hamilton) |
| This paper focuses on the skills and knowledge for communicating with data. A variety of methods of communicating and presenting data will be covered. | |||
| DATAX321 | Advanced Data Analysis | 15.0 | 24B (Hamilton) |
| This paper covers the use of statistical packages for data analysis and modelling. The emphasis is on observational rather than experimental data. The topics covered are regression modelling and its generalisations, and multivariate analysis. | |||
| DATAX322 | Probability and Stochastic Processes | 15.0 | 24A (Hamilton) |
| This paper introduces students to probability theory and stochastic processes. It covers formally the theoretical foundations of probability, random variables, statistics, stochastic processes and Markov chains. | |||
| DATAX390 | Directed Study | 15.0 | 24A (Hamilton) & 24B (Hamilton) |
| A directed study on an approved topic in Data Analytics. | |||
| DATAX391 | Undergraduate Research Project | 30.0 | 24A (Hamilton), 24B (Hamilton), 24D (Hamilton) & 24X (Hamilton) |
| Students carry out an independent research project on an approved topic under staff supervision. | |||
| DATAX397 | Work-Integrated Learning Directed Study | 15.0 | 24X (Hamilton) |
| Students carry out an independent work-related project on an approved topic under staff supervision. | |||
500 Level
| Code | Paper Title | Points | Occurrence / Location |
|---|---|---|---|
| COMPX521 | Machine Learning Algorithms | 15.0 | 24B (Hamilton) |
| This paper exposes students to selected machine learning algorithms and includes assignments that require the implementation of these algorithms. | |||
| DATAX520 | Dissertation | 45.0 | 24X (Hamilton) |
| A directed investigation and report on an approved project or study topic. | |||
| DATAX525 | Topics in Statistics | 30.0 | 24A (Hamilton) |
| This paper will discuss advanced topics in statistics. The exact topics covered could change subject to the preference and research expertise of the academic staff. Students preferences may also be taken into account. | |||
| DATAX590 | Directed Study | 30.0 | 24B (Hamilton) |
| Students have the opportunity to pursue a topic of their own interest under the guidance of academic staff. | |||
| DATAX591 | Dissertation | 30.0 | 24X (Hamilton) |
| A report on the findings of a theoretical or empirical investigation. | |||
| DATAX592 | Dissertation | 60.0 | 24X (Hamilton) |
| A report on the findings of a theoretical or empirical investigation. | |||
| DATAX593 | Statistics Thesis | 90.0 | 24X (Hamilton) |
| An externally examined piece of written work that reports on the findings of supervised research. | |||
| DATAX594 | Statistics Thesis | 120.0 | 24X (Hamilton) |
| An externally examined piece of written work that reports on the findings of supervised research. | |||
Scholarships and prizes
Selected scholarships for Data Analytics students.
New to Waikato? The International Excellence Scholarship is worth up to $10,000.
Looking for more scholarships?
Contacts
School of Computing and Mathematical Sciences
Phone:
Email: [email protected]
Website: cms.waikato.ac.nz
Facebook: https://www.facebook.com/WUcms