Brief
The program offers both curricular and extracurricular activities. The program includes interactive lectures and workshops that cover the following topics:
- interactive lectures and workshops on:
- Topics involving the application of the sustainability concept based on the green transition (Marko Ćirović, Jelena Andreja Radaković). (T1)
- Topics related to the principles and concepts of the circular economy as one of the key tools of the green transition (Marko Ćirović, Nemanja Backović, Miloš Parežanin). (T2)
- Topics related to green innovation and green entrepreneurship (Radul Milutinović). (T3)
- Topics related to the application of business analytics in the green transition (Gordana Savić, Dragana Makajić-Nikolić, Milan Radojičić, Andrijana Džamić, Isidora Gaćeša). (T4)
- Topics related to the use of AI in business analytics (Dragan Vukmirović). (T5)
- Topics related to solving case studies and presenting (Milan Okanović, Ana Miličević). (T6)
- Overview of the related industry and presentation in front of a practice-led jury panel.
Activities are organized Monday through Friday 9:00 to 16:30 with two short coffee breaks and a lunch break. On the final day, students will present their solutions.
Please note that the timetable can be subject to change at any time until the program confirmation.
The extracurricular activities offered by the program are the city tour and excursion. These activities give students a good chance to create new friendships, explore Belgrade, and find out more about its cultural heritage. All extracurricular activities are optional.
Upon completion, the participants will be able to evaluate the program.
Detailed schedule
Participant Registration
Welcome speech at FON and introduction speech
Introducing and presenting the summer school programme and presenting the home countries and schools of the participants.
Introduction speech
Professor Gordana Savić will greet all present and introduce participants of the summer school to the specifics of business analytics and its application in the green transition. She will also present the summer school objectives, purpose, and outcomes and guide the participants through all the units that should enrich their knowledge with the planned outcomes.
Coffee break
Greeen Tranzition and Sustainability
Outcomes
This theme introduces the key concepts and practical approaches for transitioning societies and organizations toward low-carbon, resource-efficient, and socially responsible development. Learning outcomes are:
- Apply green transition principles to real-world cases: Students will be able to analyze an organization/city/system through a sustainability lens (climate, resources, circularity, ESG/SDGs) and propose practical, evidence-based actions that improve environmental performance.
- Measure and communicate sustainability impact: Students will be able to choose appropriate indicators (e.g., carbon footprint, energy/water use, waste, and mobility impacts), interpret the results, and clearly communicate a basic sustainability plan or mini-report to different stakeholders.
Lunch
Circular economy
Outcomes
This theme explores how to shift from linear “take–make–waste” models to circular systems that reduce resource use, extend product lifetimes, and keep materials in circulation. Learning outcomes:
- Design circular strategies for products and services: Students will be able to map a product/service life cycle and propose circular interventions (reduce–reuse–repair–remanufacture–recycle), including business models that keep materials in use longer.
- Evaluate circular performance and trade-offs: Students will be able to select simple circularity indicators (e.g., material flows, recycled content, waste prevention), assess feasibility (cost, infrastructure, user behavior), and justify the most impactful circular options for a given case.
Coffee break
Green innovation and green entrepreneurship
Outcomes
This theme focuses on turning sustainability challenges into innovative solutions and viable ventures that create measurable environmental and social value. Learning outcomes:
- Develop and pitch a green venture idea: Students will be able to identify a sustainability problem/opportunity, generate a green innovation concept, and translate it into a basic business model (value proposition, customers, revenue/costs, partners) with a clear impact story.
- Assess viability and sustainability impact of innovations: Students will be able to evaluate a green innovation using key criteria (market need, scalability, resources/technology readiness, risks) and define measurable environmental and social impact indicators (e.g., CO₂ reduction, waste avoided, resource efficiency).
Green Tranzition and circular economy in Practice (Case study prezentation)
Belgrade guided tour
Introduction to Business Analytics
Introduction to Business Analytics
This topic introduces the fundamental concepts of business analytics and its role in supporting sustainable and green transition. Students will learn how to:
- Identify the main types of business analytics (descriptive, predictive, and prescriptive) and describe their practical applications;
- understand the role of business analytics in driving sustainability and green transition strategies;
This topic focuses on analyzing historical environmental data to evaluate sustainability performance. Students will be able to:
- understand the role of descriptive analytics in business analytics in the context of green transitions;
- interpret sustainability dashboards and key environmental performance indicators (KPIs).
Coffee break
Descriptive analytics Using MS Excel and Power BI
This topic focuses on using spreadsheets and visualization tools to summarize, analyze, and interpret historical environmental data. Students will learn how to:
- analyze environmental data such as energy consumption, carbon emissions, and resource efficiency,
- apply descriptive analytics techniques to summarize and interpret historical data through basic statistical measures with the support of a spreadsheet and visualization tools.
Lunch
Predictive analytics in Green Transition
- the fundamental concepts of predictive analytics, including regression, classification, and forecasting models.
- to understand the applications of predictive analytics in the green transition.
Coffee break
Predictive analytics Using MS Excel
This topic introduces descriptive analytics techniques and focuses on using spreadsheets to build and evaluate predictive models. Students will be able to:
- develop basic predictive models to estimate future trends and support proactive decision-making using spreadsheets.
- evaluate the accuracy and reliability of predictive analytics models with the support of a spreadsheet.
Prescriptive analytics in Green Transition
This topic emphasizes data-driven approaches for optimizing sustainable business decisions. Students will:
- understand the role of prescriptive analytics in optimizing business decisions by integrating predictive insights with optimization;
- learn how to formulate models of optimization problems related to the green transition and recommend data-driven solutions.
Coffee break
Prescriptive analytics Using MS Excel Solver
This topic demonstrates how MS Excel Solver can be used in prescriptive analytics. Students will be able to:
- design and solve optimization problems using MS Excel Solver;
- assess alternative solutions to recommend actions that enable a more efficient green transition.
Lunch
To be announced
Coffee break
Excursion
AI in Business Analytics
This theme introduces how artificial intelligence can enhance business analytics by improving prediction, decision-making, and process efficiency using data-driven methods. Learning outcomes are:
- Apply AI methods to business analytics problems: Students will be able to select and use appropriate AI techniques (e.g., classification, forecasting, clustering) to analyze business data and generate actionable insights.
- Interpret and communicate AI-driven results responsibly: Students will be able to evaluate model performance and limitations, explain results to non-technical stakeholders, and consider key ethical and data-privacy implications in business use cases.
Coffee break
Applying AI to ESG & Sustainability KPIs (Hands-On Lab) (Workshop)
This hands-on workshop trains students to use AI and analytics to clean, integrate, and analyze ESG/sustainability data in order to generate practical KPI dashboards and decision-ready insights. Learning outcomes:
- Build and operationalize ESG KPI analytics: Students will be able to prepare ESG datasets, define relevant KPIs (e.g., emissions, energy, water, waste, diversity), and create a simple KPI dashboard or reporting structure.
- Use AI to detect patterns and support decisions: Students will be able to apply basic AI/ML techniques (e.g., anomaly detection, trend forecasting, clustering) to identify risks/opportunities in ESG performance and translate findings into clear recommendations.
Lunch
Identifying Problems and Opportunities: From Empathy to Defining Solutions Workshop 1
Learning outcomes:
Students identify and clearly formulate relevant problems through exploring users’ needs and challenges in real contexts.
Students develop the ability to adopt the users’ perspective and demonstrate empathetic understanding through user journey mapping.
Coffee break
Identifying Problems and Opportunities: From Empathy to Defining Solutions Workshop 2
Learning outcomes:
Students design possible approaches to address identified problems by rationally utilising available resources and opportunities within the ecosystem.
Students strengthen their creative confidence through generating and critically evaluating user-oriented ideas.