Course Details
Topic1 Introduction to AI in Healthcare
- Understanding the Benefits of AI in Healthcare
- Interpreting Data Patterns in Healthcare
- Extracting Insights from Healthcare Data
- Case Studies:
- AI Applications in Healthcare
- Using AI for Early Diagnosis of Diseases
- AI-Powered Predictive Analytics for Patient Outcomes
Topic 2 Data Science and Business Insights
- Evaluating Data Science Solutions for Healthcare
- Managing Data Science Projects in Healthcare
- Prioritizing Data Science Projects for Maximum ROI
- Customizing Data Models for Healthcare Hypotheses
- Case Studies:
- Implementing AI for Patient Monitoring and Care
- Data Science in Drug Discovery and Development
Topic 3 Data Mining and Analysis
- Running Complex Data Mining Models in Healthcare
- Managing Organizational Capacity for Data Science Projects
- Exploring Healthcare Data Sets Visually and Analytically
- Case Studies:
- Successful Data Mining Applications in Healthcare
- AI for Predicting Disease Outbreaks
- Data Mining for Personalized Treatment Plans
Topic 4 Advanced Data Science Techniques
- Communicating the Results of Data Science Projects
- Making Recommendations Based on Data Insights
- Application of Statistics and Data Mining in Healthcare
- Tools and Techniques for Advanced Data Modeling
- Measuring the Capability of the Data Science Team
- Case Studies:
- AI in Medical Imaging for Accurate Diagnostics
- Machine Learning Models for Predicting Patient Readmission Rates
Course Info
Prerequisite:
This is a intermediate course. The following knowledge is asumed:
- Basic Python
Software Requirement:
Please install the following software prior to the class
1. Pycharm : - Install Pycharm (https://www.jetbrains.com/pycharm/download/)
2 . Install Tensorflow on Mac
Please follow this guide to install Tensorflow on Mac https://www.tensorflow.org/install/install_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 https://www.tensorflow.org/install/install_windows
HRDF Funding
Please refer to this video https://youtu.be/Kzpd-V1F9Xs
1- HRD Corp Grant Helper
How to submit grant applications for HRD Corp Claimable Courses
2- Employers are required to apply for the grant at least one week before training commences.
Employers must submit their applications with supporting documents, including invoices/quotations, trainer profiles, training schedule and course content.
3- First, Login to Employer’s e-TRIS account -https://etris.hrdcorp.gov.my
Second, Click Application
4- Click Grant on the left side under Applications
5- Click Apply Grant on the left side under Applications
6- Click Apply
7- Choose a Scheme Code and select HRD Corp Claimable Courses: Skim Bantuan Latihan Khas. Then, click Apply
8- Scheme Code represents all types of training that suit the requirements provided by HRD Corp. Below are the list of schemes offered by HRD Corp:
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Select your desired training programme.
Give an explanation on why the participant is required to attend the training. E.g., related to their tasks/ career development, etc.
Explain the background and objective of this training.
Select a relevant focus area. For Employer-Specific Courses, select ‘Not Applicable’.
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Insert MiCAS Application number
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26- Select Upfront Payment to Training Provider and key in the percentage from 0% to 30%. Then, click Save and Next
27- Complete the declaration form and select a desired officer
28- Add all the required documents, then click Add Attachment. Then, click Save and Submit Application
29- Once the New Grant Application is successfully submitted, the Grant Officer will evaluate the application accordingly. The application may be queried if additional information is required.
The application status will be updated via the employer’s dashboard, email, and the e-TRiS inbox.
Job Roles
- Data Scientist
- Healthcare Analyst
- Clinical Researcher
- Medical Practitioner
- AI Developer
- Machine Learning Engineer
- Health Informatics Specialist
- Biostatistician
- Medical Imaging Specialist
- Robotics Engineer
- Bioinformatician
- Pharmacologist
- Genetic Counselor
- Public Health Specialist
- Medical Writer
Trainers
Dr Azam: Dr Azam is an aerospace engineer with a passion on machine learning. He self-taught himself R statistical methods and has developed a machine learning course specifically for mechanical engineers; curating example case studies where traditional engineering analysis benefitted from machine learning techniques. Currently, he is involved in analyzing data from an oil platform as part of a large predictive maintenance package. He is also interested in mobile apps development and has consulted a few businesses to modernize their point of sale system using tailor-made android apps. He has supervised final year projects related to android mobile apps and one of the projects has won silver award for the best project overall.
Nero: Nero is dean of Penang School of AI, which is AI learning and sharing community in Northern Malaysia. He is Msc in Computer Imaging in Universiti Sains Malaysia. His research is mainly focusing in Video Analytic and Multiple object tracking. At the same time, he is developing computer vision application in WyseTime, a tech-startup company focus on video analytic application using deep learning technology.
Lee Cheong Loong: Lee Cheong Loong, Manager with 23 years working experience in multiple role and department, He completed HRD Corp Train the Trainer programme, HRD Corp Accredited Trainer, Microsoft Certified Trainer and CPFA Citizen Data scientist Trainer programme. with Professional certificate in Big Data & Analytics, Microsoft Office Specialist -Excel 2016 and Tableau Desktop Specialist. He also deliver training for R & Python programming, Excel Dashboard for Business analysis, Data Visualization with Tableau, and Microsoft PowerBI, and Citizen Data Scientist (OpenCertHub).