EncartaLabs

HealthCare Data Analysis with Machine Learning

( Duration: 3 Days )

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.

The HealthCare Data Analysis with Machine Learning training course 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.

By attending HealthCare Data Analysis with Machine Learning workshop, delegates will learn to:

  • 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.

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

COURSE AGENDA

1

Introduction to HealthCare Data

  • Patient Historical Data
  • DNA/RNA Sequence Data
  • Biomarkers Data
  • Medical Image Data
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.
3

Regression

  • What is Regression
  • Linear Regression
  • Multivariate Regression
  • Build Regression Model with Healthcare data
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.
5

Neural Network

  • Simple Neuron
  • Neural Network formulation
  • Learning with Error Propagation
  • Gradient Checking and Optimization
6

Build Neural Network based model to detect Breast Cancer.

7

Biomarkers

  • DNA and Protein Biomarkers
  • Classify DNA Sequence using NN.
  • Biomarker selection to detect early stage cancer
8

Hybrid machine learning model

  • What are Hybrid ML models?
  • Build Hybrid models to detect disease.
9

Improving Models

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

Encarta Labs Advantage

  • One Stop Corporate Training Solution Providers for over 4,000 Modules on a variety of subjects
  • All courses are delivered by Industry Veterans
  • Get jumpstarted from newbie to production ready in a matter of few days
  • Trained more than 50,000 Corporate executives across the Globe
  • All our trainings are conducted in workshop mode with more focus on hands-on sessions

View our other course offerings by visiting http://encartalabs.com/course-catalogue-all.php

Contact us for delivering this course as a public/open-house workshop/online training for a group of 10+ candidates.

Top