Graduate Certificate in Basics of Deep Learning
-- viewing nowThe Graduate Certificate in Basics of Deep Learning is a comprehensive course designed to provide learners with fundamental skills in deep learning. This program covers essential topics such as neural networks, convolutional networks, and recurrent networks, enabling learners to understand and apply deep learning techniques to real-world problems.
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Course Details
• Introduction to Deep Learning
• Neural Networks and Backpropagation
• Convolutional Neural Networks (CNNs)
• Recurrent Neural Networks (RNNs) & Long Short-Term Memory (LSTM)
• Deep Learning Frameworks: TensorFlow, PyTorch, Keras
• Generative Adversarial Networks (GANs)
• Deep Reinforcement Learning
• Applications of Deep Learning: Computer Vision, Natural Language Processing, Speech Recognition
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Entry Requirements
- Basic understanding of the subject matter
- Proficiency in English language
- Computer and internet access
- Basic computer skills
- Dedication to complete the course
No prior formal qualifications required. Course designed for accessibility.
Course Status
This course provides practical knowledge and skills for professional development. It is:
- Not accredited by a recognized body
- Not regulated by an authorized institution
- Complementary to formal qualifications
You'll receive a certificate of completion upon successfully finishing the course.
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