This semester, I focused on developing financial modeling skills in Microsoft Excel, using spreadsheets to analyze and evaluate real-world decisions. While I initially approached this goal through the lens of private equity, my focus evolved into building a broader foundation in financial modeling. This shift allowed me to better understand how to structure models, project revenues and costs, and analyze how different assumptions impact outcomes.

I approached this goal using the SMART framework to make my progress intentional and outcome-driven. I defined a specific objective: to build a complete financial model capable of evaluating a real investment opportunity. My progress was measurable through concrete outputs, including a fully functional model with clearly organized inputs, calculations, and outputs, as well as my ability to communicate the model effectively in a workshop setting. The goal remained achievable through consistent, hands-on practice and iterative improvement over the semester. It was relevant to my broader academic and professional interests at the intersection of finance, technology, and data-driven decision-making. Finally, it was time-bound, with a clear deadline to complete both the model and the workshop by the end of the term, which helped maintain steady progress.

Over the course of the semester, I built a simplified financial model from the ground up, organizing inputs, calculations, and outputs in a clear and logical way. This process helped me move beyond simply using Excel toward understanding how to design models that are both functional and interpretable. A key takeaway was learning how to break down complex problems into manageable components and use structured data to guide decisions.

To support this learning process, I completed several online tutorials and practical exercises focused on Excel-based financial modeling. One of the most helpful introductory resources was the YouTube video “Learn Financial Modeling Essentials in Excel,” which covered spreadsheet organization, forecasting formulas, and the foundations of financial model construction. I also completed the “Simple Leveraged Buyout (LBO) Tutorial!” tutorial, which introduced me to the mechanics of leveraged buyout modeling and helped connect Excel techniques to real-world finance applications.

As I became more comfortable with the fundamentals, I shifted my focus toward improving both the structure and flexibility of my models. I practiced separating inputs, calculations, and outputs into clearly defined sections so assumptions could be adjusted without disrupting the rest of the spreadsheet. This approach mirrors professional financial modeling standards and reinforced the importance of transparency and auditability in model design.

I also worked on building revenue projections using growth assumptions and simple scenario toggles, allowing me to quickly evaluate how changes in assumptions impacted projected outcomes. Alongside this, I strengthened my understanding of core Excel functions frequently used in finance, including IF statements, INDEX-MATCH, PMT, and basic discounting formulas. I began experimenting with sensitivity-style analysis to better understand how small changes in variables affect overall projections and investment outcomes.

Another especially valuable resource was MyOnlineTrainingHub YouTube Channel, which introduced more modern Excel practices and advanced spreadsheet functionality. These tutorials helped me think more critically about spreadsheet design, including the use of Excel Tables and dynamic formulas to improve scalability and efficiency. Exploring these modern approaches showed me how professional modeling practices continue to evolve beyond many older Excel tutorials.

I also had the opportunity to lead a workshop on financial modeling in Excel. Teaching these concepts pushed me to communicate technical ideas in an accessible way and reinforced my own understanding, while making these tools more approachable for students from different academic backgrounds.

A significant part of this experience took place while I was studying abroad in London, which added another dimension to my learning. Being in a global financial hub made the skills I was developing feel especially relevant, while also requiring me to stay disciplined and self-directed in a new environment. Balancing academics with the experience of living in London strengthened both my independence and my ability to apply what I was learning in a broader context.

Overall, this experience showed me that financial modeling is not just about Excel—it’s about developing a structured way of thinking. These skills are highly transferable across finance, economics, entrepreneurship, and data analysis.

Moving forward, I plan to build more advanced models, incorporate scenario and sensitivity analysis, and continue developing workshops that introduce students to practical financial modeling in Excel.