Mest Learning objectives 16888 ES077 After the next two lectures you should be familiar with what gradient-based optimization techniques are available understand the basics of how each technique works be able to choose which optimization technique is appropriate for your problem understand what to look for when the algorithm terminates understand why the algorithm might fail C Massachusetts Institute of Technology - Prof de Weck and Prof Willcox Engineering Systems Division and Dept of Aeronautics and Astronautics4 © Massachusetts Institute of Technology - Prof. de Weck and Prof. Willcox Engineering Systems Division and Dept. of Aeronautics and Astronautics Learning Objectives Learning Objectives After the next two lectures, you should: • be familiar with what gradient-based optimization techniques are available • understand the basics of how each technique works • be able to choose which optimization technique is appropriate for your problem • understand what to look for when the algorithm terminates • understand why the algorithm might fail