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Course Details
Day 1
Topic 1 Introduction to Medical Images
- X-ray and CT Imaging
- Magnetic Resonance Imaging
- Ultrasound Imaging
- Optical Microscopy and Molecular Imaging
Topic 2 Basic Image operation with Python
- Read and Display Image
- Covert Colour Image to Grayscale Image
- Cropping and Resizing an Image
- Rotating Image
- Histogram Equalization
- Blurring an Image
Topic 3 Texture in Medical Images
- Texture characterization – Statistical vs Structural
- Co-occurrence Matrix
- Orientation Histogram
- Local Binary Pattern (LBP)
- Texture from Fourier features
- Wavelets
- Feature extractions for Image (Medical/General)
Topic 4 Neural Network for Visual Computing
- Simple Neuron
- Neural Network formulation
- Learning with Error Propagation
- Gradient Checking and Optimization
Topic 5 Deep Learning
- What is Deep Learning?
- Families of Deep Learning
- Multilayer Perceptron
- Learning Rule
- Autoencoders
- Retinal Vessel Detection using Autoencoders
Topic 6 Stacked, Sparse, Denoising Autoencoders
- Stacking Autoencoders
- Ladder wise pre-training and End-to-End Pre-training
- Denoising and Sparse Autoencoders
- Ladder Training
- End-to-End Training
- Medical Image classification with Stacked Autoencoders
Day 2
Topic 7 Convolutional Neural Network (ConvNet)
- What is ConvNet?
- Difference between Fully connected NN and ConvNet.
- Stride, Padding, and Pooling
- Deconvolution
- ReLU Transfer Function
Topic 8 Image Classification with CNN
- Convolutional Autoencoder
- LeNet for Image Classification
- AlexNet for Image Classification
Topic 9 Improving Deep Neural Network
- Batch Normalization, Dropout
- Tuning Hyper-parameters to improve performance of NN.
- Learning Rate Annealing
- Different Cost Functions
Topic 10 Deep CNN and its application to Medical Images
- Vgg16, ResNet34, GooleNet, and DenseNet121
- Transfer Learning
- Pneumonia detection from Chest X-rays with Deep CNN.
- White blood cell classification with CNN
Topic 11 Object Localization
- Activation pooling for object localization
- Region proposal Network
- Sematic segmentation
- UNet
- Retinopathy Image segmentation with UNet
Topic 12 Spatio-Temporal Deep Learning
- Understanding Video analysis
- Recurrent Neural Network (RNN)
- Long Short Term Memory (LSTM)
- Activity recognition using 3D-CNN
- Analysis of Brain Images
Course Info
Promotion Code
Your will get 10% discount voucher for 2nd course onwards if you write us a Google review.
Minimum Entry Requirement
Knowledge and Skills
- Able to operate using computer functions
- Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)
Attitude
- Positive Learning Attitude
- Enthusiastic Learner
Experience
- Minimum of 1 year of working experience.
Target Age Group: 21-65 years old
Minimum Software/Hardware Requirement
Software:
1. Pycharm : - Install Pycharm (https://www.jetbrains.com/pycharm/download/)
2 . Install Tensorflow on Mac
Please follow this guide to install Tensorflow on Mac
Alternatively, you can enter the following commands on your Mac terminal
pip3 install tensorflow
3 . Install Tensorflow on Window
Please follow this guide to install Tensorflow on Window
Tensorflow only support Python 3.5, you can install Tensorflow in Python 3.5 the following ways:
- Install Anaconda for Windows
- Create a new Conda environment in Pycharm for Python 3.5
Hardware: Windows and Mac Laptops
SSG Training Grant
SSG TG is $15 per pax. Net fee after SSG TG is $309.82. Absentee Payroll is not eligible.
Steps to Apply Skills Future Claim
- The staff will send you an invoice with the fee breakdown.
- Login to the MySkillsFuture portal, select the course you’re enrolling on and enter the course date and schedule.
- Enter the course fee payable by you (including GST) and enter the amount of credit to claim.
- Upload your invoice and click ‘Submit’
Get Additional Course Fee Support Up to $500 under UTAP
The Union Training Assistance Programme (UTAP) is a training benefit provided to NTUC Union Members with an objective of encouraging them to upgrade with skills training. It is provided to minimize the training cost. If you are a NTUC Union Member then you can get 50% funding (capped at $500 per year) under Union Training Assistance Programme (UTAP).
For more information visit NTUC U Portal – Union Training Assistance Program (UTAP)
Steps to Apply UTAP
- Log in to your U Portal account to submit your UTAP application upon completion of the course.
Note
- SSG subsidy is available for Singapore Citizens, Permanent Residents, and Corporates.
- All Singaporeans aged 25 and above can use their SkillsFuture Credit to pay. For more details, visit www.skillsfuture.gov.sg/credit
- An unfunded course fee can be claimed via SkillsFuture Credit or paid in cash.
- UTAP funding for NTUC Union Members is capped at $250 for 39 years and below and at $500 for 40 years and above.
- UTAP support amount will be paid to training provider first and claimed after end of class by learner.
Job Roles
- Machine Learning Engineer
- Data Scientist
- Deep Learning Researcher
- AI Developer
- Neural Network Designer
- Computer Vision Engineer
- NLP Engineer (branching into deep learning)
- AI Product Manager (technical understanding)
- Robotics Engineer (with AI components)
- Bioinformatics Scientist (deep learning applications)
- Medical Imaging Specialist (AI-focused)
- Game Developer (AI-driven features)
- Predictive Analytics Specialist
- AI/ML Educator or Trainer
- Autonomous Systems Developer.
Trainers
Man Guo Chang: Man Guo Chang graduated from Nanyang Technological University, School of Electrical and Electronic Engineering, major in Computer Engineering.
He has more than 25 years of working experience in the Semiconductor field, specialized in IC Testing, Inline Electrical Testing, Product & Yield Engineering, Data Analysis, System Engineering, and Software Development. He is also an ACTA certified trainer, currently providing STEM training to adult learners in the area of Computer Vision, Internet of Things, Embedded Electronics, and Python Programming
Quah Chee Yong: Quah Chee Yong is a ACTA trainer. Chee Yong is an experienced professional who has held various Technical, Operations and Commercial positions across several industries A firm believer that AI can create a better world, he has equipped himself with the Knowledge and Skills in the fields of Data Science, Machine Learning, Deep Learning and Cloud Deployment He has a deep passion for training & facilitating and is currently a Singapore WSQ certified Adult Educator. He particularly enjoys the interactive engagements with his fellow trainers and learners.
Customer Reviews (7)
- Very good Review by Course Participant/Trainee
-
Deliver advanced course (Posted on 11/22/2020)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - will recommend Review by Course Participant/Trainee
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. (Posted on 9/28/2020)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Might Recommend Review by Course Participant/Trainee
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Students should come in the ability to set up a virtual environment and basic python so as to reduce time teaching basic programming concepts.1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment
Trainer was very comprehensive in teaching (Posted on 7/2/2019) - Might Recommend Review by Course Participant/Trainee
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Students should come in the ability to set up a virtual environment and basic python so as to reduce time teaching basic programming concepts.1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment
Trainer was very comprehensive in teaching (Posted on 7/2/2019) - Will Recommend Review by Course Participant/Trainee
-
. (Posted on 5/22/2019)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Will Recommend Review by Course Participant/Trainee
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I think we wasted some time with downloading the appropriate packages (eg. keras, torch, fastai etc), so if the pre-course instructions could include these, it will give us more time to focus on the content.1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment
Perhaps have a recap session, Q&A session, or organize a sort of alumni follow up. It is especially useful when one goes back, digest the materials and tried out in earnest all the problems and solutions. I think a small fee for that is acceptable for most of us. (Posted on 5/22/2019) - Will Recommend Review by Course Participant/Trainee
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. (Posted on 4/22/2019)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment
Write Your Own Review
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