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Fundamentals of CNNs and RNNs
This course covers fundamental concepts of convolutional neural networks (CNNs) and recurrent neural networks (RNNs), which are widely used in computer vision and natural language processing areas.
In the CNN part, you will learn the concepts of CNNs, the two major operators (convolution and pooling), and the structure of CNNs. In the RNN part, you will learn the concept and the structure of RNNs, and the two variants of RNNs, LSTMs and GRUs.
The goal of this course is to give learners basic understanding of CNNs and RNNs. Throughout this course, you will be equipped with skills required for computer vision and natural language processing.
Duration
5 Months
Institution
Sungkyunkwan University
Format
Online
Eligibility Criteria
school
Academic Foundation
A recognized Bachelor’s degree or high school equivalent required for admission into Sungkyunkwan University.
language
Language Proficiency
English proficiency required. IELTS, TOEFL, or standard medium-of-instruction certificates accepted.
Detailed Fees Breakdown
Base Tuition Fee
$75
Total Est. Investment
$75
Scholarships and early-bird waivers may apply. Contact admissions for exact institutional fees.
Academic Trajectory
Program Outcome
Graduates of the Fundamentals of CNNs and RNNs program at Sungkyunkwan University are equipped with global perspectives, ready to excel in international markets and top-tier career opportunities.