Sustainability and Data Analytics

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 Programmemes draw from the course content of the current MSc Data Science Programmeme 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 Programmeme, and is aligned with the UN 2030 agenda.

The skills and training provided by these Programmemes aim to empower individuals to help make the 2030 agenda a reality.

Program Levels

• Postgraduate Certificate

  4 core courses courses
  
  Total: 12 credits

• Postgraduate Diploma

  6 core courses courses (18 credits); 2 elective courses (6 credits)
  
  Total: 24 credits

• Masters

  6 core courses courses (18 credits); 2 elective courses (6 credits); 2 projects (12 credits)
  
  Total: 36 credits

Program Goals

1. Provide an understanding of the Sustainable Development Goals (SDGs), identifying opportunities for data science solutions and econometrics for sustainability analysis.
2. Equip students with advanced machine learning concepts, real-world data analysis, and data manipulation skills.
3. Help students develop practical data analysis, communication, visual presentation, dashboard building, research methods, and problem-solving abilities for a sustainable future.
4. Cover research methods, SDG research, critical evaluation, and problem-solving abilities.

Program Objectives

1. Evaluate SDGs and challenges and communication of opportunities for data science/machine learning.
2. Explain machine learning and its application to sustainability issues.
3. Communicate machine learning model results to stakeholders.
4. Write Python Programmes for data manipulation and visualization of sustainability data.
5. Build data dashboards using Excel and Google Sheets
6. Interpret architecture diagrams for data pipelines.
7. Apply machine learning concepts to address issues in sustainability.
8. Write technical documents for effective communication of research findings.
9. Interpret official SDG publications and research using descriptive statistics and distributions.
10. 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