Requirements
- Basic knowledge in Operations Research and Optimization
- Basic programming skills in Python
Description
This course will guide you on what optimization is and what metaheuristics are. You will learn why we use metaheuristics in optimization problems as sometimes, when you have a complex problem you'd like to optimize, deterministic methods will not do; you will not be able to reach the best and optimal solution to your problem, therefore, metaheuristics should be used.
This course covers information on metaheuristics and four widely used techniques which are Simulated Annealing, Genetic Algorithm, Tabu Search, and Evolutionary Strategies. By the end of this course, you will learn what Simulated Annealing, Genetic Algorithm, Tabu Search, and Evolutionary Strategies are, why they are used, how they work, and best of all, how to code them in Python! With no packages and no libraries, learn to code them from scratch!! You will also learn how to handle constraints using the penalty method.
Please feel free to ask me any question! Don't like the course? Ask for a 30-day refund!!
The ideal student should have basic knowledge in Operation Research and basic programming skills.
Real Testaments -->
1) "I can say that this is the best course I've had on Udemy ! Dana is a very good instructor. She not only explains the problems and the coding, but also reassures you and remove the fears you might have when learning complex concepts. For someone with a business background, this topic was close to a nightmare ! I highly recommend this course for anyone interested in learning about Metaheuristics. Again, big THANK YOU Dana ! :)" -- Logistics Knowledge Bank, 5 star rating
2) "I am half way through the course. What I learnt so far is far beyond what I expected. What I really liked is the applicability of the examples to real world problems. The most exciting feature in the course is the hands on, what you learn will be implemented in python and you can follow every single step. If you did not understand, the instructor is there to help. I even felt like it is a one to one course. Thanks a lot to the instructor." -- Ali, 5 star rating
3) "It is a great introduction to Metaheuristics. The course deserves five stars for the overall information on this topic. The instructor is talented and knowledgeable about the optimization problems. I recommend the course for someone looking to solve an optimization problem." -- Abdulaziz, 5 star rating
4) "Nice course that really does explain Metaheuristics in a very practical way. Highly recommended!" -- David, 5 star rating
Who is the target audience?
- Anyone who wants to learn about metaheuristics
- Anyone who wants to learn Genetic Algorithm
- Anyone who wants to learn Simulated Annealing
- Anyone who wants to learn Tabu Search
- Anyone who wants to learn Evolutionary Strategies
- Anyone who wants to code metaheuristics in Python
- Anyone who wants to learn how to handle constraints
