Sustainability and Data Analytics
Application deadline
November 30, 2024
Starts on
January, 2025
Duration
8 weeks, online
Program fee
US$10,000
Overview
The certificate, diploma, and MSc Sustainability and Data Analytics aim to produce graduates who are competent in using data science and its related skills to solve real-world problems related to the SDGs and move the world to a more sustainable future.
The programmes draw from the course content of the current MSc Data Science programme but focuses and expands it to solve problems on sustainability. It is designed to advance The University’s strategic goal of Access, both geographically and to candidates without traditional higher education qualifications who want to 'ladder up' from the Graduate Certificate to the Master's level programme, and is aligned with the UN 2030 agenda. The skills and training provided by these programmes aim to empower individuals to help make the 2030 agenda a reality.
Sustainability and Data Analytics
Program Levels
Postgraduate Certificate in Sustainability and Data Analytics
4 core courses
Total: 12 credits
Postgraduate Diploma in Sustainability and Data Analytics
6 core courses (18 credits); 2 elective courses (6 credits)
Total: 24 credits
MSc in Sustainability and Data Analytics
6 core courses (18 credits); 2 elective course (6 credits); 2 projects (12 credits)
Total: 36 credits
Admissions Criteria
Postgraduate Certificate
Candidates without a bachelor’s degree with a minimum of 2 years work experience and qualifications in mathematics and programming at the equivalent of A’Level.
Postgraduate Diploma
At least a bachelor’s degree from a recognized University with a minimum GPA of 2.5 OR A Graduate Certificate in a relevant area of study
MSc
At least a bachelor’s degree from a recognized University with a minimum GPA of 2.5 OR Graduate Diploma in relevant area of study
Program Goals
- Provide an understanding of the Sustainable Development Goals (SDGs), identifying opportunities for data science solutions and econometrics for sustainability analysis.
- Equip students with advanced machine learning concepts, real-world data analysis, and data manipulation skills.
- Help students develop practical data analysis, communication, visual presentation, dashboard building, research methods, and problem-solving abilities for a sustainable future.
- Cover research methods, SDG research, critical evaluation, and problem-solving abilities.
Program Objectives
- Evaluate SDGs and challenges and communication of opportunities for data science/machine learning.
- Explain machine learning and its application to sustainability issues.
- Communicate machine learning model results to stakeholders.
- Write Python programs for data manipulation and visualization of sustainability data.
- Build data dashboards using Excel and Google Sheets
- Interpret architecture diagrams for data pipelines.
- Apply machine learning concepts to address issues in sustainability.
- Write technical documents for effective communication of research findings.
- Interpret official SDG publications and research using descriptive statistics and distributions.
- Implement econometric techniques in Python for real-world SDG data analysis.
SDG Focus
- #8 - Decent work and economic growth
Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all - #9 - Industry, innovation and infrastructure
Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation - #10 - Reduced inequalities
Reduce inequality within and among countries - #17 - Partnership for the goals
Strengthen the means of implementation and revitalize the Global Partnership for Sustainable Development
Faculty
Kris Manohar
Dr. Osman Mohammed
Mr Paul Malhar
Mr Izzy Mnzaman Rahaman
Mr. Kyle De Freitas
Dr. Letetia Addison
