Freeman’s MBA Lifelong Learning

This course delves into the strategic implications of artificial intelligence in the business world. Students will explore how AI can be utilized to attain and protect competitive advantage of the firm, foster innovation, improve systems and operations, including decision-making processes. The curriculum covers topics such as the role of AI in business strategy, the impact of AI on organizational change, and the ethical considerations of AI implementation. Through case studies, discussions, and lectures students will develop a comprehensive understanding of how to effectively integrate AI into business operations, equipping them to lead in the dynamic field of management and innovation.

In today's dynamic business landscape, data literacy is no longer optional for strategic leaders. This course equips senior managers and executives with the skills to interpret and leverage data analytics for high-impact decision-making. Rather than focusing on technical execution or coding, the course emphasizes critically evaluating data-driven insights, interpreting analytical models, and applying them to core strategic challenges. You will engage with real-world business scenarios involving innovation management, competitive advantage, and corporate strategy, using tools from predictive and prescriptive analytics, machine learning, network analysis, and AI. The course enables you to become a more effective strategic thinker—able to frame the right questions, assess the validity of analytic recommendations, and communicate data-driven insights with clarity and conviction to stakeholders across the organization.

The financial industry is undergoing a rapid transformation driven by artificial intelligence (AI) and machine learning (ML). These technologies are revolutionizing financial services, enhancing decision-making, and creating new business models. As financial institutions increasingly adopt AI-driven solutions, there is a growing demand for leaders who understand the strategic and practical applications of AI in finance. AI technologies are reshaping the financial sector, impacting areas such as risk management, trading, investment strategies, fraud detection, and customer experience. For executive-level professionals, understanding these technologies is essential for making informed decisions, driving innovation, and maintaining a competitive edge.

This course introduces managers to the use of spreadsheets as a business modeling tool. The overarching goal is to teach organizational leaders to use spreadsheets and data visualization to analyze models and data for integrated decision making across multiple domains including operations, finance, marketing, accounting, and strategy. The course will cover:

1. Data Essentials in Excel – formulas, filters, reference functions, pivot tables & charts, and data tables
2. Deterministic Optimization – linear/nonlinear formulation and programming, optimal solution
3. Decision-Making under Uncertainty – sensitivity analyses, decision criteria, probability distributions using simulation
4. Automation – reading and writing macros
5. Data Visualization - using both Excel and PowerBI

This is a hands-on course with real-life applications on various business analytics problems.

This condensed course helps students to understand and practice the full entrepreneurial process—from opportunity identification to scaling and exit—while explicitly learning where artificial intelligence can aid execution and where human judgment remains essential. Students will learn to build ventures in an “AI-enabled” way: using AI to increase speed and breadth in research, hypothesis generation, prototyping, messaging, and analytics, while maintaining rigorous standards for evidence, ethics, and strategic decision-making. A central theme is disciplined entrepreneurship under conditions of high uncertainty and high automation. Students will practice using AI tools as a partner or “co-pilot” (for drafting, synthesis, scenario testing, and iteration) but will also engage with the human elements AI cannot replace: deep customer empathy, taste and prioritization, leadership, trust-building, and accountability for risk (privacy, IP, bias, and regulatory exposure).

This condensed course examines how artificial intelligence is changing the practice of growth strategy while grounding students in core growth strategy theory and disciplined strategic decision-making. Building from the core ideas in Cliff Farrah’s Growing the Top Line, the course begins with foundational frameworks for understanding how firms create revenue growth through market expansion, customer insight, positioning, innovation, channel development, and execution discipline. The course then explores how AI is changing the cost, speed, and cadence of strategy work. As information, analysis, and idea generation become easier and less expensive, the scarce source of value shifts from producing strategic options to exercising judgment about which options should be pursued. Students will work directly with AI toolkits to support market sensing, customer and competitive analysis, strategic option generation, scenario development, and communication of growth recommendations. These tools will be treated not as substitutes for strategic thinking, but as accelerators that require careful human oversight.

Artificial intelligence transforms the way we write, speak, and visualize ideas. This course introduces students to AI tools and their applications in various communication fields, including business writing, media production, personal branding, and speaking. Students will gain hands-on experience using AI for writing, image generation, and presentation design while examining ethical and creative challenges posed by emerging technologies.

This course examines the many decisions involved in collecting, analyzing, interpreting, and presenting data. Through a mix of theoretical and practical exercises, students will learn to recognize common pitfalls that can lead to misunderstandings and misrepresentations in data analysis. Examples will be drawn from both business and non-business settings, using a mix of analytic tools, including AI, to develop a deep understanding of the practical challenges of real-world data analysis and the broader implications of this process for business, policy, and society.

This course examines the foundations of investment theory and practice. It begins by elaborating the concepts of risk and risk aversion, wealth allocation between risky and risk-free assets, and optimally risky portfolios. The course proceeds to develop various asset-pricing models, paying special attention to the CAPM and APT. The course will also examine the concept of market efficiency and review the empirical evidence for and against efficiency. The second half of the course examines theories and strategies for managing investment portfolios. This includes surveying how securities are actually traded and cleared. It then examines theories of active portfolio management ranging from the Peter Lynch approach to more formal models such as the Treynor-Black model. Issues of asset allocation, extended (e.g. global and real asset) diversification, and investment company organization and policy formation are studied. The course concludes with a study of portfolio performance measurement.

Corporations face a variety of risks including interest rate risk, commodity price risk, foreign exchange rate risk, counter party default risk and political risk in addition to the usual business risks of their chosen fields of operation. This course analyzes the corporate decision to hedge (or not to hedge) focusing on how these decisions maximize shareholder value. The course explores ways in which firms manage their exposure to product market and financial risk and provides a balanced treatment of commodity price, interest rate, and currency risks. Topics include swaps, financial futures, FRAs, options and other recent innovations in the derivatives markets. The issue of counter party default risk and risk management approaches such as VAR (value-at risk) are also studied.

Through case analysis, this course explores ways to value different types of business enterprises. The course emphasizes discounted cash flow methods of valuation, though other methods, such as the method of multiples, the venture capital method, and real options are also introduced. Students develop and practice valuation skills, such as financial forecasting, cash flow measurement, discount rate estimation and continuing value calculation. In addition, students work with a variety of corporate situations, such as LBO's, IPO's, spin-offs, and mergers, in which valuation plays a key role.

This course is designed to provide experienced executives with practice-oriented, nuanced, in-depth knowledge of the various aspects of the corporate strategy of the firm. "Corporate strategy" means managing the firm's scope – in other words, managing a corporation as a portfolio of businesses: What business units should the company have in order to maximize the shareholders' value? How should it acquire new lines of business? How should it divest the units it no longer wants? What should be the extent of the units' autonomy? In this class, students will improve their understanding of what makes a portfolio of businesses under a single corporate umbrella more or less valuable. Students will also develop and hone the decision-making tools for properly structuring and executing acquisitions and alliances under different business situations.

Examines the key aspects of leading a successful organizational change. The course analyzes both successful and unsuccessful change management efforts, allowing students to practically apply readings and discussions to individual organizational experiences. The course will build a framework for leading a successful organizational change.

This course provides experienced executives with practice-oriented, powerful analytical frameworks for better managing their company's innovation process and increasing its success rate of bringing innovations to market. "Managing innovation" means creating effective internal processes to sense innovation trends, to invest in the "right" portfolio of innovation projects, and to better understand the factors causing innovations to succeed or fail in the market. How can companies sense future innovations and shape these innovation opportunities to their advantage? Which projects should we invest in to create a portfolio that balances our company's needs for both short-term profits and long-term growth? What implications do disruptive technologies have for our company and its industry? How likely is an innovation to restructure the basis of competition in our industry and threaten our current competitive advantage?

Focuses on the structure and processes of management, particularly those of a global organization, and simulates upper-level management activities of the global enterprise. Course objectives include developing an integrated understanding of strategic and operational decision-making in a global enterprise from a general management perspective. Managing the Global Enterprise is a 4-credit course with classes in-person at our uptown campus and a 7-day international trip.

Note: Special pricing is required for this course due to travel costs and company visits. If you are interested in this course, please reach out to Danielle Martin at dmartin15@tulane.edu.

Classes are held at the Uptown Campus in the Goldring/Woldenberg Business Complex. We provide comprehensive enrollment and academic support. All technical and prep requirements are provided immediately upon registration. Students are responsible for the course materials and additional fees that may apply.

To ensure we can provide our signature support and have your materials ready, registration closes exactly 14 days prior to the class start date.

MBA Alumni are expected to engage at the same level of rigor as current students. This includes adhering to attendance policies, active participation in classroom dialogue, and completing all required assessments.

We offer a preferred MBA alumni tuition rate of $900 per credit hour exclusively for Freeman MBA alumni. Payment is due after registration. If you are seeking employer reimbursement, we provide a corporate invoicing option.

Yes. While this initiative is non-degree granting, you will receive academic credit, a formal grade, and an official record with the university registrar for every course you complete.