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Course Details
Course Details
Topic 1 Introduction to Deep Learning
Machine Learning vs Deep Learning
Deep Learning Methodology
Overview of Tensorflow Keras
Install and Run Tensorflow Keras
Basic Tensorflow Keras Operations
Topic 2 Neural Network for Regression
What is Neural Network (NN)?
Loss Function and Optimizer
Build a Neural Network Model for Regression
Topic 3 Neural Network for Classification
One Hot Encoding and SoftMax
Cross Entropy Loss Function
Build a Neural Network Model for Classification
Topic 4 Convolutional Neural Network (CNN)
Introduction to Convolutional Neural Network?
ImageDataGenerator
Image Classification Model with CNN
Data Augmentation and Dropout
Topic 5 Transfer Learning
Introduction to Transfer Learning
Applications of Pre-Trained Models
Fine Tuning Pre-Trained Models
Topic 6 Recurrent Neural Network (RNN)
Introduction to Recurrent Neural Network (RNN)
LSTM and GRU
Build a RNN Model for Time Series Forecasting
Build a RNN Model for Sentiment Analysis
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:
You can download and install the following software:
Hardware: Windows and Mac Laptops
Job Roles
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
Trainers
Richard Wan: Richard Wan is a ACTA certified trainer. Richard Wan has more than 30 years of experience in software development in various computer disciplines, including computer vision, communication and digital publishing.
Technical expertise includes: Windows, Linux developments with C, C++, Delphi (Object Pascal), Visual Studio, OpenCV. Embedded system programming including microcontrollers, Arduino, Pi, BeagleBone etc.
Ken Yuen: Ken Yuen is a ACTA certified trainer. He has more than 10 years of experience working as an instructor, Application Development Engineer, Technical Consultant and Project Manager. He is an MOE-Registered Instructor teaching STEM programs for past 3 years such as Arduino, Micro:bits and robotics to schools and libraries based on the smart nation initiative roadmap.
He completed his Diploma in Electronic Engineering at Singapore Polytechnic and graduated with Bachelor of Electrical and Electronics Engineering from Nanyang Technological University and certified PMP (Project Management Professional).
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
Solomon Soh Zhe Hong: Solomon is ACTA certified and has trained and coached over 100 professionals in the area of data science, python programming and coding. Solomon is a Certified AI Engineer Associate by AI Singapore and holds certifications in Alibaba Cloud Architect and Alteryx respectively. Solomon interests include Reinforcement Learning, Natural Language Processing and Time-Series analysis.
Review
Customer Reviews (105)
- Great trainer and i appreciate his knowledge and skills, Thank you Review by Course Participant/Trainee
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Going slow and in detail in RNN / CNN (cover less but cover in depth) (Posted on 6/10/2018)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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This course should have 1st day for preparation of tools to be used for hands-on. So can make this course fro 3 days (Posted on 6/10/2018)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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Nil (Posted on 6/10/2018)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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2 days course could be too short to have meaningful depth in the subject (Posted on 6/10/2018)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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Be more specific to student’s request1. 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
I am from banking industry and I hope the trainer can share more with me regarding building credit scoring models to predict defaults (Posted on 4/30/2018)
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