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Instructor-led Classroom Adult Training in Singapore - Modular Fast Track Skill-Based Trainings

HealthCare Data Analysis with Machine Learning

Digital Health is rapidly being comprehended as the future of Healthcare. The healthcare sector transformed by the ability to record massive amounts of healthcare related information. Delivery of the quality healthcare relies on the ability to analyse and understand the data. Machine Learning (ML) algorithms allow dealing with verities of structured and unstructured data. ML provides a way to automatically find the pattern within the data, which provide better insights to improve the healthcare outcomes.

This two days of training will cover different modalities of healthcare data, basic statistical analysis of the data using python (Numpy/Pandas), machine learning algorithms, supervised leaning, unsupervised learning, ML-based model building with practical healthcare datasets, and Neural Network. One can use these skills to analyse different types of data to improve the quality of critical diagnosis. 

Course Highlights

  • Understanding different Health Care Data.
  • Machine Learning (Supervised and Unsupervised Learning).
  • Breast Cancer detection using ML.
  • Early prediction of Diabetes from patient historical data.
  • Autism Screening model using ML.
  • DNA/RNA sequence classification.
  • Design Biomarkers for Cancer detection.
  • Fully connected Neural Network.
  • Heart Disease prediction with Neural Network.
  • Early stage malaria detection with Neural Network.

Certificate

All participants will receive a Certificate of Completion from Tertiary Courses after achieved at least 75% attendance.

Funding and Grant Applications

No funding is available for this course

Course Code: C1018

Course Booking

$598.00 (GST-exclusive)
$639.86(GST-inclusive)

Course Date

Course Time

* Required Fields

Course Cancellation/Reschedule Policy

We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% to participants.
Note the venue of the training is subject to changes due to class size and availability of the classroom.
Note the minimal class size to start a class is 3 Pax.


Course Details

Day 1

Topic 1 Introduction to HealthCare Data

  • Patient Historical Data
  • DNA/RNA Sequence Data
  • Biomarkers Data
  • Medical Image Data

Topic 2 Machine Learning

  • Supervised Learning
  • Classification vs Regression
  • Classification Models (KNN, Naïve Bayes, SVM, etc.)
  • Decision Tree
  • Build Classification Model with Diabetes and Heart Disease data.

Topic 3 Regression

  • What is Regression
  • Linear Regression
  • Multivariate Regression
  • Build Regression Model with Healthcare data

Topic 4 Unsupervised Learning and Dimension reduction

  • What is Unsupervised Learning?
  • Principal Component Analysis (PCA)
  • Dimension reduction of Healthcare data using PCA.
  • Calculate the importance of different features.

Day 2

Module 5 Neural Network

  • Simple Neuron
  • Neural Network formulation
  • Learning with Error Propagation
  • Gradient Checking and Optimization

Module 6 Build Neural Network based model to detect Breast Cancer.

Module 7 Biomarkers

  • DNA and Protein Biomarkers
  • Classify DNA Sequence using NN.
  • Biomarker selection to detect early stage cancer

Module 8 Hybrid machine learning model

  • What are Hybrid ML models?
  • Build Hybrid models to detect disease.

Module 9 Improving Models

  • Overfitting and Underfitting
  • Tuning Hyper-parameters to improve performance Models.
  • Different Cost Functions
  • Early stage malaria detection

Course Admin

Prerequisite

This is a intermediate course. The following knowledge is assumed:

  • 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

Tensorflow only support Python 3.5, you can install Tensorflow in Python 3.5 the following ways:

Who Should Attend

  • Data Scientists
  • Data Analysts
  • Machine Learning Engineers and Developers

Trainers

Deep Learning TrainerDr. Sudipta Samanta received his Ph.D. for his research in the field of computational Biophysics in 2009. He has more than 9 years research experience as a scientist. His current interests include Machine Learning, Deep Learning, Health Care Data analysis, and computer simulation. He is also the founder of "Baby Lion Organic medicinal Farm".

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