Strategic Financial Management: Tools, Analysis, and Decision-Making

The Microdegree offers a comprehensive understanding of how financial analysis and data-driven tools support corporate strategy and drive value creation. The programme integrates classical financial management, modern technologies, and real-world decision-making to develop strategic thinking and analytical precision.

The courses are delivered by international faculty members and industry practitioners who bring together academic excellence, analytical rigour and a practical perspective on strategic finance.

The learning journey follows a cyclical structure – starting with data acquisition and analysis, moving into financial modelling and investment strategy, and culminating in effective financial communication and capital acquisition. Each course contributes to the development of a well-rounded competence profile, helping learners understand financial decisions from both corporate and investor perspectives.

The learning approach is highly practical: contact sessions and group work are combined with independent assignments. Real-life case studies are used alongside tools such as Excel, Power BI and Python. Discussions, simulations and project-based work create a learning experience that is at once analytical, creative and strategic.

This microdegree is not only about acquiring knowledge; it is designed to shape your professional identity at the intersection of business thinking and financial leadership.

The programme is intended for participants who already have the ability to read and interpret financial statements and who understand the core principles of corporate finance, including investment decisions, the functioning of capital markets, and the relationship between risk and return.

Data Tools for Financial Management –  16 h in classroom, 62 h independent studies  – 3 ECTS
Master the data skills modern finance runs in Python, from the ground up. This hands-on course takes you from messy spreadsheets to AI-powered analysis, with every concept explained in plain English before you write a line of code. You'll clean and analyze real market data, build statistical models and regressions, pull live data from APIs, scrape the web, push results into Excel and Power BI dashboards, and even put large language models like Claude and GPT to work inside your own scripts. By the end, you'll be able to build a complete data pipeline from raw file to polished, credible insight, and bring the analytical edge that today's finance leaders are expected to have.
Lecturer: Samuli Saarinen- PhD Student / AML Analyst

To support a smooth start to the programme, we will offer an optional introductory workshop on 17 October. During the workshop, participants can get help with installing the required software and Python libraries and receive a short practical introduction to Python. The workshop is recommended for those who feel they would benefit from additional preparation. Participants who are already comfortable with these tools do not need to attend. 

Financial Modelling –  16 h in classroom, 88 h independent studies  – 4 ECTS
This course provides in-depth knowledge and hands-on skills in building dynamic financial models to support decisions on capital budgeting, dividend policy, and M&A. Learners construct integrated pro forma statements and dashboards in Excel and Power BI, incorporating data-driven assumptions and scenario analyses. The course also emphasizes ethical decision-making, ESG considerations, and the ability to clearly communicate complex financial outcomes.
Lecturer: Alvin Kamienski – PhD professor and consultant with extensive experience bridging business and education; has taught finance, strategy, and economic freedom in the U.S. and internationally

Investment Decisions  –  16 h in classroom, 62 h independent studies  – 3 ECTS
This course builds a solid foundation in investment principles, risk management, and portfolio construction, enabling participants to evaluate asset classes and make sound investment decisions. Students learn how macroeconomic trends and capital market mechanisms affect portfolio strategies, and how to assess risk-reward trade-offs. By formulating a personal investment philosophy, participants align financial goals with real-world market behavior and investor logic.
Lecturer: Valeria Kiisk – PhD, Partner at Redgate and Head of the Capital Markets Working Group at FinanceEstonia.

Financial Storytelling for Capital Acquisition –  24 h in classroom, 106 h independent studies  – 5 ECTS
As the capstone course of the microdegree, this module challenges students to combine financial modeling, investment strategy, and data storytelling to pitch capital acquisition strategies. Teams develop investor-focused presentations and reports based on rigorous analysis, valuation, and market insight. The final project simulates a real-world investor pitch, enhancing strategic thinking, persuasive communication, and team collaboration in high-stakes finance scenarios.
Lecturer: John Paul Broussard – PhD, finance professor and researcher of artificial intelligence, machine learning, and big data applications in finance.