Description
Mathematical Decision Making: Predictive Models and Optimization, the training course Mathematical Decision Making: Predictive Models and Optimization is published by TTC Academy. Not long ago, executives faced with complex problems made decisions based on experience and intuition. But now there is a better way. In recent decades, mathematics and computer science have perfected previously top-secret techniques for predicting the best possible outcomes when faced with conflicting options. This discipline is known by many names such as analysis, operations research, linear and non-linear programming, management science, but its purpose is simple: to use quantitative methods to help business managers, civil servants, investors, scientific researchers. , and problem solvers of all kinds for better decision making.
These same techniques can be used in retirement planning, stock portfolio analysis, budget forecasting, health care allocations, public relations, marketing and advertising, and many other tasks for companies large and small. The uses are truly endless! Mathematical decision-making had its first rigorous tests during World War II, when the Allies used top-secret operations research to protect convoys, improve the aim of anti-aircraft fire, and find weaknesses in Allied bombers. After the war, private industry enthusiastically embraced operations research, but these new methods were expensive, computationally slow, and only experts could use the algorithms. This situation has changed dramatically, and today anyone with a home computer and a spreadsheet program can harness the power of these methods to solve practical problems. The trick is knowing what you can do and how to do it.
What you will learn
- Pricing: Costco has become one of the top retailers in the world by combining membership fees with bulk sales. A mathematical technique called Genetic Algorithm shows the advantages of this strategy as well as the optimal prices for charging.
- Scheduling: Using nonlinear scheduling, many airlines use scheduling software that can find the optimal solution to unexpected disruptions—from weather to mechanical problems to crew availability. and save millions of dollars in operating costs.
- Suggestion: Simulation models can take a lot of the guesswork out of competitive bidding for a project. By running repeated simulations against competitors, a bidder can come up with a bid that has a good chance of winning the job, while still making a profit.
- Queuing: Any process that reflects the behavior of waiting lines is called queuing. Markov analysis shows how a small increase in the input to a system can have a major impact on the waiting time. This method also shows amazing solutions to eliminate long waits.
Who is this course suitable for?
- Managers eager to make better decisions – whether in business, technical tasks
- Professionals who wish to advance in their careers by mastering a proven method of problem solving.
- Those who work with spreadsheets and graphical presentations and need to be able to separate good data from bad
- Students of business, mathematics, finance, marketing, healthcare, engineering, urban planning and many other fields.
- Math lovers who are curious to study a field that often opposes calculus instead of complex functions with simple boundary conditions.
- Students who want to strengthen their critical thinking skills with important analytical techniques
Specifications of the course Mathematical Decision Making: Predictive Models and Optimization
- Publisher: TTC
- teacher : Scott P. Stevens
- English language
- Education level: all levels
- Number of courses: 24
- Training duration: 12 hours and 29 minutes
Chapters of the Mathematical Decision Making: Predictive Models and Optimization course
Pictures
Sample video
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