Graduate Diploma in Data Analytics (Level 7)
Schedule
click here
Duration
1 Academic Year
Delivery
Hybrid
Campus
Auckland CBD
Credits
120
Fees Domestic
$7,774
Fees International
This programme is not available for international students
| Data Analytics sits at the crossroads of technology, statistics, and strategy. Our Graduate Diploma in Data Analytics (Level 7) at NZSE equips students with the analytical and technical expertise to collect, clean, and interpret data from diverse sources — helping organisations improve productivity and efficiency. Through practical, hands-on projects and collaborative learning, you’ll master key tools and techniques such as Python, R, SQL, statistical analysis, machine learning, and business intelligence. Graduates leave ready to transform complex data into high-level meaningful insights that drive business success. |
GDDA604 – Data Collection and Analysis
This course will provide students the knowledge to utilise various methods of collecting data from a wide range of sources. Students will explore different ways of transforming, analysing, and interpreting data to make data-driven business decisions.
Technology used:
Python, SQL
GDDA612 – Data Transformation and Management
This course equips students with the skills to collect, clean, and transform data from various sources, preparing it for processing. Students will learn to import pre-processed data into data stores, query and manipulate data sets, and export data in appropriate formats for further use.
Technology used:
Python, SQL/NoSQl, BeautifulSoup, Scrapy, or Selenium
GDDA707 – Advanced Data Engineering
This course provides the skills to examine and apply data-modeling technologies, relational and non-relational data models, extraction, transformation, and loading (ETL) operations, and data engineering on big data platforms.
Technology used:
Python, SQL, ETL, Cassandra, Hive, MongoDB, Apache Hadoop ecosystem (HDFS, Yarn, Zookeeper, Kafka, Spark)
GDDA708 – Machine Learning and AI
This course provides students with the knowledge and skills to apply supervised and unsupervised machine learning algorithms in Artificial Intelligence (AI). Students will learn to evaluate and optimise these algorithms to improve business decisions and AI-based applications.
Technology used:
Python, TensorFlow, Scikit-learn
GDDA709 – Big Data Analytics
This course provides the opportunity to investigate, evaluate and implement different big data technologies.
Technology used:
Hadoop, Yarn, HDFS, MapReduce, Hive, Apache Spark, Machine learning, Spark Machine Learning libraries
GDDA713 – Capstone Project
The Capstone Project allows students to apply critical thinking, creativity, problem-solving, communication, and technical skills to solve a real-world problem. It showcases their industry knowledge and abilities, addressing a client brief and fulfilling the graduate profile outcomes.
Technology used:
SQL, Python, AI and Machine Learning, Big data analytics, Statistical models
GDDA716 – Emerging Trends and Technologies in Data Analytics
This course provides students with an opportunity to explore emerging trends and technologies in the field of data analytics. Students will apply research methodologies, analyse issues surrounding the trends and technologies, conduct SWOT analysis for applicability to a business to produce research output, and communicate research outputs to technical or non-technical audiences.
- For Domestic Students
- Applicants must hold a relevant and recognised Degree Level qualification equivalent to at least 360 credits at NZQA Level 7 or equivalent. Applicants aged 20 years or above who have not met the General Admission and Entry Requirements may be eligible for special admission. Talk to us if you want to know more
- For International Students
- Applicants must hold a relevant and recognised Degree Level qualification equivalent to at least 360 credits at NZQA Level 7 or equivalent. Applicants aged 20 years or above who have not met the General Admission and Entry Requirements may be eligible for special admission. Talk to us if you want to know more
- International English Language Test System (IELTS) Academic score of 6.0 with no individual band score lower than 5.5; or equivalent
- Hold a valid study visa
- Data Analyst
- Database Developer Administrator
- Social Media Data Analyst
- Quantitative Analyst
- Marketing Data Analyst
- Business Intelligence Analyst
- Data Insights Analyst
- Research Analyst
- Data Warehouse Engineer
- Machine Learning Analyst
- Quantitative Analyst
Gain access to higher level study at our partner universities*
Take your data career to new heights
You’ll complete a capstone project that challenges you to apply your critical thinking, creativity, and technical skills to solve a real-world business problem. This hands-on experience, combined with the comprehensive knowledge gained throughout the programme, prepares you for a wide range of roles including Data Analyst, Business Intelligence Analyst, Marketing Data Analyst, Machine Learning Analyst, and Data Warehouse Engineer. Graduates leave equipped to turn complex data into actionable insights that are highly sought after across industries.
Need help making your decision?
Schedule and fees
Auckland CBD
Start Date
- 21/07/2025
End Date
- 19/06/2026
Fees *(GST inclusive)
NZD $7,774
Payment options
- Pay in 2 instalments of ——— per certification; or
- Weekly payment options available to ——–.
- Join our alumni network
- Create a job-ready portfolio
- Learn from industry experts
- Live classes
- NZQA Certified
- Gain project experience
- Weekly payment options
- 10-weeks mentored work experience
This programme is not available for international students.
Looking for more?
Check out more of our technolgy courses here.
Further study options
- Pathways to graduate and post-graduate programmes at universities, in New Zealand or overseas, or to Te Pūkenga or Private Training Establishments (PTEs) in New Zealand.