Artificial Intelligence Engineer (AI Engineer) Online Course
This 11-month AI Engineer Online Course, jointly developed by IBM and Simplilearn, equips learners with skills in Artificial Intelligence, Generative AI, and Machine Learning. It constitutes 7 core courses, plus 1 elective, total 8 courses.
Covering essentials like prompt engineering, ChatGPT, Deep Learning, NLP, and Computer Vision, the program includes hands-on labs, capstone projects, and live masterclasses from IBM experts. Participants gain proficiency in Python, NumPy, scikit-learn, and GANs, while earning up to 9 certificates, including IBM credentials.
Course Duration
Total: 11 months
Course Fee
HKD11,622
Benefits
- Integrated virtual lab (with Python 3.10, Jupyter licenses) already included in course fee
- Live online masterclasses delivered by IBM experts
- Capstone and industry-relevant projects
- Gain Expertise in AI, ML, Deep Learning, and Prompt Engineering
- A comprehensive AI engineering course for professionals
Course Overview
Course 01 – Essentials of Generative AI, Prompt Engineering & ChatGPT
Course 02 – Programming Essentials
Course 03 – Python for Data Science (IBM)
Course 04 – Data Science with Python
Course 05 – Machine Learning using Python
Course 06 – Deep Learning Specialization
Course 07 – Deep Learning Specialization
Electives:
- Deep Learning with TensorFlow (IBM)
- Advanced Deep Learning and Computer Vision
- Natural Language Processing (NLP)
- Advanced Generative AI
- Industry Master Class – AI
Tools Covered in the Course
Python, ChatGPT, Keras, NumPy and Scikit-learn package
Elective-Specific Tools:
TensorFlow


Awards upon Successful Completion
- obtain up to a total of up to 9 certificates, including the overall AI Engineer certificate.
- IBM constituent courses: IBM certificate
Access Period of Course
1 year from date of enrolment
Deep Learning Specialization Online Course
This comprehensive Deep Learning 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.
By the end of the course, you will have solid foundation in Deep Learning principles and the ability to build and optimize Deep Learning models effectively using Keras and TensorFlow.
Course Duration
Total: 42 hours (2 hours self-paced learning videos; 40 hours live virtual class)
Benefits
- Differentiate between Deep Learning and Machine Learning and understanding 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
Course Overview
- Course 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
Tools Covered in the Course
- TensorFlow 2
- Keras
- PyTorch
Award upon Successful Completion
- Certificate from Simplilearn
Access Period of Course
1 year from date of enrolment

Advanced Deep Learning & Computer Vision
This comprehensive course provides in-depth knowledge and practical skills in the field of computer vision and advanced deep learning techniques. You will delve into various topics, including image formation and processing, Convolutional Neural Networks (CNNs, object detection, image segmentation, generative models, optical character recognition, distributed and parallel computing, and deploying deep learning models. By the end of the course, you will have the expertise to tackle complex computer vision challenges and successfully deploy deep learning models in various applications
Benefits
- Gain job-ready skills for AI research, autonomous systems, or medical imaging roles.
- Work on deployment-ready projects
- Earn a certificate validating expertise in state-of-the-art vision AI
Award upon Successful Completion
Certificate from Simplilearn
Access Period of Course
1 year from date of enrolment