December 15, 2025
08:30
Hilton DoubleTree West End or equivalent hotel
See our homepage for more detailed information about these NTUiTiV Differences.
This immersive 5-day, 100% computer-based programme equips participants with cutting-edge analytical, modelling, and predictive techniques using the full power of Microsoft Excel®. Through Problem-Based Learning, participants tackle real-world challenges—ranging from financial risk modelling to engineering optimisation—while mastering advanced tools such as Monte Carlo simulations, Genetic Algorithms, Markov Models, and Machine Learning principles.
The course bridges theory and practice, ensuring delegates leave with the ability to analyse complex systems, model outcomes, optimise performance, and confidently apply AI-related methods to real business scenarios.
Modern organisations face an explosion of data from the Internet-of-Things, Big Data, and ever-increasing business demands for precision, efficiency, and predictive power. Traditional methods no longer suffice.
This course empowers professionals to:
By mastering these skills, participants position themselves as analytical leaders capable of driving evidence-based decision-making.
This course is ideal for professionals who want to:
Typical participants include managers, data analysts, engineers, operational leaders, and decision-makers eager to unlock the full power of data for business transformation.
Over five intensive days, the course covers:
• Day 1: System Modelling & Introduction to Simulation
Building models for financial, production, and engineering systems using deterministic methods and conventional optimisation techniques.
• Day 2: Simulation & Introduction to Optimisation
Regression analysis, machine learning fundamentals, and predictive modelling for real-world scenarios such as resource allocation and risk estimation.
• Day 3: Advanced Optimisation & AI Methods
Multi-variate optimisation, visualisation of functions, and AI-based techniques such as Genetic Algorithms.
• Day 4: Deep Dive into Optimisation & Multi-Objective Problems
Advanced linear, non-linear, and genetic optimisation for complex systems including supply chain optimisation.
• Day 5: Binary Logic & Probability-Based Modelling
Risk minimisation using binary decision models, Monte Carlo simulations, and Markov Chains for predictive analytics in uncertain environments.
Delegates will leave with the ability to create models, simulate behaviours, optimise outcomes, and integrate machine learning into practical business contexts.
⭐️⭐️⭐️⭐️⭐️ (5/5)
“The professor’s depth of knowledge was astounding—he explained complex concepts with such clarity. I gained practical skills in machine learning and Monte Carlo simulations that I can immediately apply to my work. The hands-on exercises were simply brilliant.”
— Fatima, Data Analyst, Finance Sector
⭐️⭐️⭐️⭐️⭐️ (5/5)
“This was the best technical training I have ever attended. The instructor made advanced optimisation techniques feel accessible and exciting. I especially enjoyed learning Genetic Algorithms through real business problems—it was eye-opening.”
— Michael, Operations Manager, Manufacturing
⭐️⭐️⭐️⭐️⭐️ (5/5)
“An exceptional course! The speaker combined academic expertise with real-world application perfectly. I loved the problem-based learning approach—it kept everything relevant and practical.”
— Thabo, Engineering Supervisor, Energy Sector