Lecture Time: 20 credit hours
Course Description:
This course is designed for anyone who is interested in computational intelligence. The course will give introduction to genetic algorithms, deep learning and its development tools. Emphasis will be placed on the conceptual understanding, what we can do with the methods, and what are typical issues have been successfully addressed already. Suitable participants for this course are anyone who has little background knowledge about computer science and programing skills and has the interesting to have a peep into the world of deep learning.
Venue:Tencent Meeting
Topics and Schedule:
Date | Content | Time |
April 10th | Course Introduction and GA Basis | 9:00-10:40 a.m. |
April 17th | Introduction to Multiple Objective Genetic Algorithms | 9:00-11:35 a.m. |
April 24th | Multiple GA and Acceleration with GPU Computing | 9:00-11:35 a.m. |
May 8th | Introduction to Tensorflow, Keras and Anaconda | 9:00-11:35 a.m. |
May 15th | Introduction of Deep Learning/Classification | 9:00-11:35 a.m. |
May 22nd | CNN(Convolutional Neural Networks) | 9:00-11:35 a.m. |
May 29th | RNN(Recurrent Neural Network) | 9:00-11:35 a.m. |
JOHN (RUNWEI) CHENG is a research scientist with extensive industry experience in high-performance computing on heterogeneous computing platforms. Before joining the oil and gas industry, John worked in the finance industry for more than ten years as an expert in computational intelligence, providing advanced solutions based on genetic algorithms hybridized with data mining and statistical learning to solve real world business challenges. His recent book, entitled Professional CUDA C Programming, published by Wiley in 2014, has been ranked as the top one among 41 best parallel computing books of all time. As an internationally recognized researcher in the field of genetic algorithms and their application to industrial engineering, John has co-authored three books. John’s first book, Genetic Algorithms and Engineering Design, published by Wiley in 1997, is still used as a textbook in universities worldwide. John has a wide range of experience in both academic research and industry development, and is gifted in making complex subjects accessible to readers with a concise, illustrative, and edifying approach. John earned his doctoral degree in computational intelligence from the Tokyo Institute of Technology.
