In setting up these outlines we assume an academic course for students of exact sciences, e.g., computer science, artificial intelligence, mathematics, engineering, and alike, with a practical flavour. Obviously, a different audiance (biology students or a business course) requires another setup. Additionally, the duration of the course is also crucial is determining how much material can be treated. To this end we specify a course at three levels, basic, extended, and full. These are indicated by the following colour scheme:
 
 

Basic
Extended
Full

 

Subject	Corresponding book sections	Corresponding slides
Introduction to EC	Chapter 1	Introduction.ppt
Evolutionary Algorithms	Chapter 2 (available as pdf file)	What_is_an_EA.ppt
Genetic Algorithms	Chapter 3	Genetic_Algorithms.ppt
Evolution Strategies	Chapter 4	Evolution_strategies.ppt
Evolutionary Programming	Chapter 5	Evolutionary_programming.ppt
Genetic Programming	Chapter 6	Genetic_programming.ppt
How to work with EAs	Chapter 14	Working_with_EAs.ppt
Parameter control in EC	Chapter 8	Parameter_control.ppt
Multimodal & multiobjective problems	Chapter 9	Multi.ppt
Memetic (or hybrid) algorithms	Chapter 10	Memetic_Algorithms.ppt
Constraint handling	Chapter 12	not on-line yet
Theory	Chapter 11	Theory.ppt
Classifier systems	Chapter 7	not on-line yet
Coevolution	Section 13.2	not on-line yet
Interactive evolution	Section 13.3	evol-art.ppt
Nonstationary optimisation	Section 13.4	not on-line yet