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Life Sciences and HealthCare Analytics Course in Porur

Launch your career in LSHC Analytics with our certification program in Life Sciences and HealthCare Analytics course. Learn Statistical Analysis, Machine learning, Predictive Analytics, and many more.
  • Get Trained by Trainers from ISB, IIT & IIM
  • 40 Hours of Intensive Classroom & Online Sessions
  • 60+ Hours of Practical Assignments
  • 2 Capstone Live Projects
  • 100% Job Placement Assurance
Life Science and Health Care Analytics course reviews - 360digitmg
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Life Science and Health Care Analytics course reviews - 360digitmg
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  • Life Science and Health Care course with IBM certificate
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  • Life Sciences and HealthCare Analytics Course in  Porur with SUNY
  • Life Sciences and HealthCare Analytics Course in  Porur with NEF
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"Innovation starts with insight and life science companies strive to pursue innovative solutions to address today’s challenges. A HealthCare analyst in Price Waterhouse Coopers (PWC) earns 6 lakhs per annum." - (Source). Analytics is an essential part of Life Sciences and HealthCare because it increases the potential for better treatment and medication. Phenomenal progress in the field of drug development, gene therapy, and wearable fitness trackers are some of the transformations seen in the life sciences sector. Today Patients are increasingly involved in their HealthCare and demand transparency, convenience, and personalized services. With Analytics in Life Sciences and HealthCare Course, companies are trying to keep up with the pace of the customer by leveraging the insights derived from the data strategically to their advantage. The amount of data available to the pharma companies today is like a treasure trove of information used to create value and new metrics from the wealth of data at their disposal.

Life Sciences and HealthCare

healthcare analytics course  in Porur- 360digitmg

Total Duration

1 Month

healthcare analytics course pre-requisite  in Porur- 360digitmg

Prerequisites

  • Computer Skills
  • Basic Mathematical Knowledge
  • Analytical Mindsets

HealthCare Analytics Course Overview

The training in Life Sciences and HealthCare Analytics course will equip you with research and analytical skills that will change the HealthCare landscape. Data has been around us for centuries but the skill to collect, organize, and visualize this data is making all the difference. Analytics when used in the Life sciences and HealthCare arena can result in numerous benefits like enhancing the health delivery system, improving the quality and safety of patients, lowering costs, and optimizing business operations. Launch your career in the booming HealthCare analytics market with the pioneering Life Sciences and HealthCare Analytics Certification Program. Designed for HealthCare practitioners, IT business analysts, and data scientists interested in the HealthCare domain provides industry-leading training in data analytics and AI.

This program is designed to have the right blend of Statistical Analysis, Predictive Modelling, and Artificial Intelligence in making human health better by taking proactive decisions. Following the trends in the broader HealthCare industry in the US, 360DigiTMG has developed a certification program in Life Sciences and HealthCare Analytics.

What are the Life Sciences and HealthCare Analytics?

Life sciences and health care analytics is a process where clinical data is studied and analyzed to provide tools for expert advice and proactive care of the patients. It is considered to be an integral part of the health care management system. Companies today are adopting data analytics and leveraging insights to manage a patient’s health outcomes. Huge databases are created with the information of the patient’s current health issues and using Analytical tools extensive study is implemented to prepare a predictive model. This model facilitates the future HealthCare of the patient and allows better decision making based on the evidence of his past HealthCare reports. This also helps pharmaceutical companies predict the future trends of the treatment and bring efficacy to the life science industry by moving from treatment to preventive measures to early intervention.

HealthCare Analytics Course Learning Outcomes

Analytics in Life Sciences and HealthCare has become an important part of HealthCare management. It is helping the HealthCare sector blend the booming data collected from various sources like bedside sensors, bio-monitor and other Internet of Things devices to generate data insights into a refined easy to understand model that can predict the future health of the patient and allow better decision making for doctors and health care professionals and to produce knowledge-based solutions for real-world challenges. But, a widening gap between the demand-supply of skilled professionals in the field of Life Sciences and HealthCare Analytics is creating challenges for public and private HealthCare systems. This program provides students an opportunity to explore a wide variety of careers in the HealthCare and Life Sciences field. Learn more about HealthCare and life sciences and how it impacts our world. Progress in the field technology, science, digital data, and augmented intelligence are transforming the traditional health care models. The curriculum provides extensive knowledge of the new elements of the HealthCare industry. Identify the various data generation sources and understand the different types of analytical tools used to develop the ability to foresee the challenges in a clinical environment. Students will gain expertise in areas like predictive and prescriptive analytics, data acquisition, Data Mining, and HealthCare information management systems.

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

Block Your Time

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40 hours

Classroom Sessions

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60 hours

Assignments

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60 hours

Live Projects

Who Should Sign Up?

  • Internal Auditors
  • CFO/Director/Head of Accounting
  • Business Analysts
  • Data Analysts
  • Banking and Accounting Analysts
  • Certified Financial Analysts
  • Credit Analysts
  • Financial Advisors
  • Math, Science and Commerce Graduates
  • IT Security officials, IT Admin (Network, Firewall, System Admin), IT professionals
  • Mid-level Executives
  • Information Security
  • Information Law

Life Sciences and Healthcare Analytics Course Modules

This course is aimed to highlight the importance of Life Sciences and HealthCare Analytics. It covers concepts dealing with HealthCare data including IoT sensor data. Learn to analyze and interpret HealthCare data effectively and understand the rich data structures contained in Electronic Health Records (EHR). This module will also help the learners to gather the requisite Python, R skills to analyze HealthCare data such as EHR, MIMIC, etc. This module also gives an insight into various data models that exist in Life Sciences and HealthCare Data. Gain knowledge on how to decipher and assess designs of data models using Entity-Relationship (ER) diagrams. You will also get into the heart and soul of the Data Science program along with predictive modeling for hospital management. This course in Life Sciences and HealthCare Analytics will fill in the gap for those who are interested in this challenging and ever-evolving field.

This module serves as an interesting primer for the uninitiated into the world of LSHC domain. Learn about the different sub-domains and how data science is empowering each of these domains. Get ready to deep dive into Life Science and Healthcare Industry, Sectors and Domains.

Welcome to the eclectic world of healthcare data. Understand the rich data structures contained in Electronic Health Records (EHR), work hands on MIMIC II data and other types of data like images from radiology, pathology, etc. Also Understand about healthcare IoT sensors data.

This module will give students the opportunity to understand the 4Ws of the healthcare data life cycle: What, Who, When, Why. Get a deeper understanding of the lifecycle to prepare for analyses that follow in subsequent modules.

As the name suggests, this module will help the learners to gather the requisite Python, R skills to analyze healthcare data such as EHR, MIMIC, etc.

This module will provide insights into various data models that are existing in Life Sciences and Healthcare Data. Learners can expect to gain knowledge on how to decipher and assess designs of data models using Entity-Relationship (ER) diagrams to contrast their individual merits and enunciate how to utilize them in providing Healthcare and Bio-statistics models, 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

Utilize patient historical data, current diagnosis and treatment and other life style and behavioral indicators to predict whether a patient is likely to get re-admitted to hospital and take preventive actions.

This module gives a basic introduction to the Natural Language Processing (NLP) on clinical trials data. Learners can expect to gain pragmatic toolsets to extricate data stored in the EMRs (Electronic Medical Records).

Use MultiLayer Perceptron to build predictive analytic capabilities using the EHR and other types of healthcare data. Use CNN models to build a prediction model to predict cancer using DICOM images. Understand about limitations of Deep Learning models in Life Science & Healthcare.

This module describes how we can leverage Deep Learning networks to analyze panoramic dental x-rays and automatic segmentation of mandibles. This is a fast and accurate method and will help in diagnosis and registration of dental records.

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How we prepare you
  • Life Science and Health Care training with placements in Porur
    Additional Assignments of over 60+ hours
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    Resume and LinkedIn Review Sessions
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    Job Placements in Life Sciences and HealthCare Fields
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    Unlimited Mock Interview and Quiz Session
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    Hands-on Experience in Live Projects
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