課程編號: CPD0122/2025
類別
GPM: General and Professional Matters
H&S: Health and Safety including Occupational Safety and Health
OTM: Environment, Information Technology, Quality and Other Technical Matters not directly related to a Trainee's own discipline
課程名稱
Deep Learning Specialization Online Course
類別
GPM
日期
1 - 31 Jan 2025
時間
** 40 hours Live Virtual Class, 2 hours Self-Paced Learning Videos
主辦單位
PTI Professional Development Limited (Authorised Sole Distributor for HKSAR of Simplilearn)
地點
Online
費用
*Free; Trial Account for One Week
簡介

Deep Learning is one of the key areas of AI. This course is one of the constituent courses of our course “AI Engineer”, offered jointly by Simplilearn and IBM.

 

This comprehensive course provides knowledge and skills to deploy deep learning tools using AI / Machine Learning frameworks effectively. Learners will explore fundamental concepts & practical applications of Deep Learning, while gaining clear understanding of distinctions between Deep Learning and Machine Learning.

 

The course covers wide range of topics, including Neural Networks, forward and backward propagation, TensorFlow 2, Keras, performance optimization techniques, model interpretability, Convolutional Neural Networks (CNNs), transfer learning, object detection, Recurrent Neural Networks (RNNs), autoencoders, & creating neural networks in PyTorch.

 

By the end of the course, you will have solid foundation in Deep Learning principles and ability to build and optimize Deep Learning models effectively using Keras and TensorFlow.

目標
  • Differentiate between Deep Learning and Machine Learning and understand their respective applications
  • Gain comprehensive understanding of different types of neural networks
  • Master concepts of forward propagation and backward propagation in deep neural networks (DNN)
  • Obtain introduction to modeling and learn techniques for improving performance in Deep Learning models
  • Comprehend hyperparameter tuning & model interpretability
  • Learn about dropout and early stopping techniques and their implementation
  • Gain expertise in convolutional neural networks (CNN) and object detection
  • Grasp fundamentals of recurrent neural networks (RNN)
  • Understand basics of PyTorch & learn how to create neural network using PyTorch
內容
  • Introduction to Deep Learning
  • Artificial Neural Networks
  • Deep Neural Networks
  • TensorFlow
  • Model Optimization and Performance Improvement
  • Convolutional Neural Networks (CNN)
  • Transfer Learning
  • Object Detection
  • Recurrent Neural Networks (RNN)
  • Transformer Models for Natural Language Processing (NLP)
  • Getting Started with Autoencoders
  • PyTorch
語言

English

備註

*Total: Up to 100 free accounts, on first-come-first-served basis.  Each month, maximum 20 trial accounts.

 

**Online video (Self-paced Learning or SPL) – Can Start immediately upon registration; Live Virtual Classes (LVCs)

Few batches to choose. After enrolment, pls. select & register on LMS (learning management system))

 

  1. One week access to Learning Management System from date of activation of LMS.
  2. Total: Up to 100 free accounts, on first-come-first-served basis.
  3. Each month, maximum 20 trial a/c.
  4. Subject to T & Cs
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