Build predictive business strategies using AI, forecasting, optimization, simulation, and quantitative decision models.
Learn to anticipate demand, allocate resources, evaluate competitors, and make strategic decisions under uncertainty.
This Specialization develops practical capabilities for using predictive intelligence in operations, markets, competitive strategy, and investment planning. You'll explore machine learning forecasting, mathematical optimization, resource scheduling, demand sensing, agent-based simulation, reinforcement learning, game theory, and business wargaming.
You'll also examine probabilistic scenario planning, stochastic models, Monte Carlo simulation, and real options analysis to evaluate strategic investments beyond traditional DCF methods. Applications span supply chains, workforce planning, logistics, healthcare, energy, retail, manufacturing, competitive intelligence, and capital investment.
By completing the Specialization, you'll be able to evaluate predictive models, optimize constrained resources, analyze competitive scenarios, assess uncertainty, value strategic flexibility, and recommend adaptive business strategies supported by quantitative evidence.
Applied Learning Project
Learners will work on applied business scenarios involving AI-driven demand forecasting, resource allocation optimization, competitive strategy simulations, and investment evaluation under uncertainty. Through practical exercises using predictive analytics, mathematical optimization, business wargaming, and real options analysis, they will assess operational constraints, compare strategic alternatives, and recommend data-driven decisions that improve business efficiency, resilience, and long-term value.
