Page 24 - De_Anza_College_Community_Ed_Winter-Spring_2021_Catalog
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 WINTER/SPRING 2021
 MACHINE LEARNING
TO DEEP LEARNING
– BEGINNING TO
INTERMEDIATE (Grades 9-12) (580*)
This course provides a broad introduction to machine learning, data mining
and statistical pattern recognition, as
well as how to build deep learning networks. Students will gain foundational knowledge of machine learning algorithms and get practical experience in building neural networks in TensorFlow and Keras in Google Colaboratory.
They will also learn about convolutional networks, SGD, Adam, Dropout, BatchNorm and more.
Instructor: Jasneet Matta has a master’s degree in information technology from Mumbai University and has taught students in grade school through college. She thrives on teaching students to grow socially and academically, while helping them gain self-confidence through motivation and encouragement.
Class requirements: Tablet or computer with internet capability
Cost: $215
Dates and times: Jan. 16, 23 and 30, Feb. 6, 13 and 27, March 6 and 13 (eight Saturdays; no class on Feb. 20), 12:30-1:50 p.m.
MACHINE LEARNING TO DEEP LEARNING – INTERMEDIATE TO ADVANCED
(Grades 9-12) (581*)
Students in this course will continue their exploration of machine learning, data mining and statistical pattern recognition, as well as how to build deep learning networks. Building on their basic knowledge of machine learning concepts, students will leran more about deep neural networks and gain practical experience in building with TensorFlow and Keras in Google Colaboratory. Participants will also review some research papers and critique.
Instructor: Jasneet Matta has a master’s degree in information technology from Mumbai University and has taught students in grade school through college. She thrives on teaching students to grow socially and academically, while helping them gain self-confidence through motivation and encouragement.
Class requirements: Tablet or computer with internet capability
Cost: $215
Dates and times: March 20 and 27, April 3, 17 and 24, May 1, 8 and 15 (eight Saturdays; no class on April 10), 12:30-1:50 p.m.
 24 *Use the class number (after each course title) when registering online.














































































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