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Life Sciences and HealthCare Analytics Course in USA

Be a part of the exciting and thriving Healthcare Analytics domain with our path-breaking Life Sciences and Healthcare Analytics Certification Program. This program is uniquely designed to cater to the ever-changing requirements of Healthcare professionals, Business Analysts in the IT industry and Machine Learning professionals in the Healthcare industry by focusing on relevant skills and technologies.

Live Instructor Led Online Training: 40 hours

Life Sciences, Healthcare Analytics Course Overvie

This course is meticulously designed to proportionately combine Statistical Analysis, Predictive Modeling, Machine learning and Deep Learning to facilitate better delivery of healthcare. Enterprises all over the world in the healthcare sector are fully utilizing Analytics powered by Artificial Intelligence thereby enhancing their productivity and innovative edge. 360DigiTMG has conducted extensive research on the current trends and probable future trends and designed the Certification Program in Healthcare Analytics. It is highly recommended for IT Business Analysts, Data Scientists, and Healthcare practitioners.

Course Details

Life Sciences, Healthcare Analytics Learning Outco

Work with various data generation sources
Understand and interpret electronic health record (EHR) data types and structures
Become proficient in analysing clinical Healthcare data
Differentiate among descriptive, predictive and prescriptive analytics
Apply machine learning techniques on Healthcare and other clinical data
Arrive at commensurate clinical and scientific interpretations of the conducted analytics
Foresee some of the challenges faced while implementing analytics solutions in complicated clinical environments

Life Sciences & Healthcare Analytics Course Module

The purpose of this module is to introduce the exciting world of LSHC - the various sub-domains and the impact of Data Science. We will briefly talk about the life sciences market size and prepare our learners for an in-depth dive into the industry with relevant examples and use cases. It also describes the advent of Big Data in Life Sciences and how that has changed the landscape.

This module will introduce the different types of healthcare data like the rich data structures contained in Electronic Health Records (EHR). Work with MIMIC- II data and other types of data like images from radiology, pathology, etc.

The focus of this module is to address the 4Ws of Healthcare Data Lifecycle - Who, What, Where and When. It also gives a deeper appreciation of Analytics in Healthcare and the Life Sciences domain.

Using the popular Python and R programming languages, this module will enable learners to analyze the healthcare data including EHR and MIMIC- II datasets. They will also learn how to use Python to work with Big data in the field of LifeSciences.

The purpose of this module is to introduce the different Data Models prevalent in Life Sciences and Healthcare Data. Students will be exposed to Entity- Relationship diagrams and enunciate how to utilize them in providing Healthcare and Bio-statistics models. It will help learners in understanding the Genomics Exploratory Data Analysis, Differential Expression Levels, Normalization, and Batch Effects of the data.

  • a. Genomics - DNA, RNA (Next Generation Sequencing Data Analysis), Gene MicroArray Gene Expression Data Analysis
  • b. Proteomics - Deal with Proteomics Data Analysis, Drug Resistance and Drug Repurposing Data Analysis
  • c. Metabolomics - Molecular-level (Abundance and Intensity values) Data Analysis, Identifying Biomarkers, etc.

This module gets into the heart and soul of the Data Science program. We start from basic statistics and progress to regression models, unsupervised and supervised learning models.

  • a. Basic Statistics, Hypothesis Testing and Regression Models
  • b. Unsupervised Machine Learning Techniques
  • c. Supervised Machine Learning Algorithms

This module will help in building a predictive model to determine if a patient is likely to get re-admitted based on historical data, current diagnosis, treatment, lifestyle and behavioral indicators which will ultimately help take preventive measures.

This module introduces Natural Language Processing techniques and how they can be applied to clinical trial data. Students will also be exposed to some toolsets used in real-life scenarios and will be able to extract information stored in Electronic Medical Records (EMRs).

This module introduces students to the Multi-Layer Perceptron (MLP) which is the most common version of Artificial Neural Networks (ANNs). Students will also learn how they can be used to predict on EHR and other types of healthcare data. They will also predict a model that can detect cancer from DICOM images using Convolutional Neural Network (CNN) models. Finally, this model will inform the students about the limitations of Deep Learning Models in the Life Sciences and Healthcare Domain.

In this module, students will learn how to take advantage of Deep Learning Architectures to analyze and extract insights from panoramic dental x-rays to facilitate the segmentation of mandibles automatically. Students will see that this method is accurate and pretty quick in diagnosing dental records.

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LifeSciences and Healthcare Analytics market has the potential to scale up to $33 billion by 2024.

(Source: www.marketsandmarkets.com)

Block Your Time

healthcare analytics course - 360digitmg

40 hours

Classroom Sessions

healthcare analytics course - 360digitmg

60 hours

Assignments &
e-Learning

healthcare analytics course - 360digitmg

60 hours

Live Projects

Who Should Sign Up?

  • IT Engineers
  • Data and Analytics Managers
  • Business Analysts
  • Data Scientists
  • Healthcare Practitioners
  • Clinicians and Physicians
  • Healthcare Administrators
  • Life Science Graduates
  • Research Scholars and Post Doctorates

Life Sciences and HealthCare

lefe sciences & healthcare course - 360digitmg

Total Duration

1 Month

lefe sciences & healthcare analytics course pre-requisite- 360digitmg

Prerequisites

  • Computer Skills
  • Basic Mathematical Knowledge
  • Analytical Mindsets

Tools Covered

python for healthcare analytics courser for healthcare analytics courser studio for healthcare analytics coursejupyter for healthcare analytics course

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Limited seats available.

Book now to avoid disappointment.

healthcare analytics course models - 360digitmg

Life Sciences, Healthcare Analytics Panel of Coach

healthcare analytics trainers

Bharani Kumar Depuru

  • Areas of expertise: Data analytics, Digital Transformation, Industrial Revolution 4.0
  • Over 14+ years of professional experience
  • Trained over 2,500 professionals from eight countries
  • Corporate clients include Hewlett Packard Enterprise, Computer Science Corporation, Akamai, IBS Software, Litmus7, Personiv, Ebreeze, Alshaya, Synchrony Financials, Deloitte
  • Professional certifications - PMP, PMI-ACP, PMI-RMP from Project Management Institute, Lean Six Sigma Master Black Belt, Tableau Certified Associate, Certified Scrum Practitioner, AgilePM (DSDM Atern)
  • Alumnus of Indian Institute of Technology, Hyderabad and Indian School of Business
Read More >
 
healthcare analytics trainers

Sharat Chandra Kumar

  • Areas of expertise: Data sciences, Machine learning, Business intelligence and Data visualisation
  • Trained over 1,500 professional across 12 countries
  • Worked as a Data scientist for 14+ years across several industry domains
  • Professional certifications: Lean Six Sigma Green and Black Belt, Information Technology Infrastructure Library
  • Experienced in Big Data Hadoop, Spark, NoSQL, NewSQL, MongoDB, R, RStudio, Python, Tableau, Cognos
  • Corporate clients include DuPont, All-Scripts, Girnarsoft (College-dekho, Car-dekho) and many more
Read More >
 
healthcare analytics trainers

Nitin Mishra

  • Areas of expertise: Data sciences, Machine learning, Business intelligence and Data visualisation
  • Over 20+ years of industry experience in data science and business intelligence
  • Trained professionals from Fortune 500 companies and students at prestigious colleges
  • Experienced in Cognos, Tableau, Big Data, NoSQL, NewSQL
  • Corporate clients include Time Inc., Hewlett Packard Enterprise, Dell, Metric Fox (Champions Group), TCS and many more
Read More >
 
healthcare analytics certification - 360digitmg

Certificate

Earn a certificate and demonstrate your commitment to the profession. Use it to distinguish yourself in the job market, get recognised at the workplace and boost your confidence. The Life Sciences and HealthCare Certificate is your passport to an accelerated career in LSHC industry.

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FAQs for Life Sciences & Healthcare Analytics

This course just assumes some basic computer familiarity and analytical mindset. It definitely helps if the learner has some background in clinical data, SQL and Programming languages such as Python and R. Knowledge of HealthCare industry is expected for better understanding.

This course is specifically catered to learners intending to either begin or advance their careers in the healthcare industry. As such, you will be exposed to highly relevant healthcare data.

You will be exposed to EHR (electronic health records), MIMIC-III database and many more datasets that are unique to the healthcare industry.

Ideally, for the purposes of this course, we have already procured and hosted the necessary datasets (samples), but if some learners are interested in how all of the Data Engineering work is done, it can be offered as a separate (or an addendum) course.

Different organisations use different terms for data professionals. You will sometimes find these terms being used interchangeably. Though there are no hard rules that distinguish one from another, you should get the role descriptions clarified before you join an organisation.

With growing demand, there is a scarcity of data science professionals in the market. If you can demonstrate strong knowledge of data science concepts and algorithms, then there is a high chance for you to be able to make a career in this profession.

 

360DigiTMG provides internship opportunities through Innodatatics, our USA-based consulting partner, for deserving participants to help them gain real-life experience. This greatly helps students to bridge the gap between theory and practical.

There are plenty of jobs available for data professionals. Once you complete the training, assignments and the live projects, we will send your resume to the organisations with whom we have formal agreements on job placements.

We also conduct webinars to help you with your resume and job interviews. We cover all aspects of post-training activities that are required to get a successful placement.

After you have completed the classroom sessions, you will receive assignments through the online Learning Management System that you can access at your convenience. You will need to complete the assignments in order to obtain your data scientist certificate.

You will be attending 40 hours of classroom and/or virtual instructor-led sessions. After completion, you will have access to the Learning Management System for three months for recorded videos and assignments. Also you will have to spend another month after the classroom sessions to complete the live project.

If you miss a class, we will arrange for a recording of the session. You can then access it through the online Learning Management System.

We assign mentors to each student in this program. Additionally, during the mentorship sessions, if the mentor feels that you require additional assistance, you may be referred to another mentor or trainer.

No, the cost of the certificate is included in the program package.

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