Inteligência Artificial: Algoritmos de Otimização em Python

Explore the world of optimization algorithms within Artificial Intelligence (AI)! This course delves into the powerful techniques used to solve complex problems and find optimal solutions in various fields. Discover practical applications of optimization in everyday business scenarios.

Key Concepts & Applications:

• Solving Complex Problems: Learn how optimization algorithms tackle intricate challenges, focusing on finding the best possible outcomes.
• Real-World Examples: See how optimization is applied to:
  • Scheduling: Dynamically create teacher schedules to maximize classroom utilization and teacher availability.
  • Logistics: Optimize delivery routes for transportation companies to reduce costs and improve efficiency.
  • Finance: Identify the most profitable investment strategies.
  • Airline Optimization: Find the best flight combinations for groups of travelers to minimize travel expenses and waiting times.
  • Resource Allocation: Efficiently assign students to dormitories based on their preferences.

What You'll Learn:

This hands-on course provides a step-by-step implementation of core optimization algorithms:

• Random Search: A foundational approach to problem-solving.
• Hill Climb: A simple yet effective method for finding local optima.
• Simulated Annealing (Recozimento Simulado): A powerful technique for escaping local optima and finding global solutions.
• Genetic Algorithms: Inspired by natural selection, these algorithms evolve solutions over time.

Practical Projects:

You'll apply these algorithms to solve two detailed case studies:

1. Airline Flight Optimization: Optimize flight itineraries for six friends traveling to the same city, minimizing ticket costs and airport wait times. We'll compare the results of each algorithm.
2. Limited Resource Optimization: Develop an algorithm to allocate students to dormitories based on their preferences, maximizing satisfaction.

Implementation Details:

• Python Programming: Gain practical experience implementing these algorithms using Python.
• No External Libraries: Learn to code the algorithms from scratch, utilizing only Python's built-in features.
• Complete Algorithms: By the end of the course, you'll have four fully functional optimization algorithms ready for use in your own projects.

Target Audience:

This course is suitable for:

• Beginners entering the fields of Artificial Intelligence and optimization algorithms.
• Intermediate learners seeking a refresher and deeper understanding of core concepts.

Ready to advance your career? Join us and master the art of optimization!