Certificate Course in
Life Sciences and HealthCare Analytics Course in USA
- 40 Hours of Intensive Classroom & Online Sessions
- 60+ Hours of Practical Assignments
- 2 Capstone Live Projects
- 100% Job Placement Assistance
Academic Partners & International Accreditations
"LifeSciences and Healthcare Analytics market has the potential to scale up to $33 billion by 2024." - (Source). USA healthcare companies have decided to move from traditional methods to analytical applications such as genomics analytics, imaging analytics, Supply chain management, Automation, Blockchain, Artificial Intelligence, Natural Language Processing (NLP), etc. The companies which have adopted advanced technologies have reached success with revenue generation from $4.5 billion to $5.5 billion and are ready to invest $1.2billion every year to build advanced capabilities related to data analytics. This kind of approach gains the trust of the patients and helps in improving healthcare services in the near future. Thus, creating a bundle of opportunities for Healthcare Analysts or Life Sciences professionals with Analytical skills.
Life Sciences and HealthCare
- Computer Skills
- Basic Mathematical Knowledge
- Analytical Mindsets
Life Sciences Healthcare Analytics Course Overview
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.
Life Sciences, Healthcare Analytics Learning Outco
360DigiTMG offers the best training in Life Sciences and Healthcare Analytics in the USA by industry stalwarts. Healthcare analytics course is built as per the requirements of the Healthcare sector, it includes all the relevant technologies where students should be well educated to become a Professional Healthcare Analyst or Data Scientist. This certification program is designed specifically for the people who are health care practitioners and have knowledge of Life sciences. Students will be exposed to EHR data types, analyze clinical data. Learn about applications of Machine learning technologies. Able to provide solutions for complicated clinical environments. The Healthcare sector is in the stage of transformation from traditional to digital data-driven. Healthcare apps are going to be launched, AI and Machine Learning technologies are going to be incorporated into drug discovery, diagnosis, and treatment. There is a huge scope for lIfe Sciences practitioners who have analytical skills in the long run.
Block Your Time
2 Live Projects
Who Should Sign Up?
- IT Engineers
- Data and Analytics Manager
- Business Analysts
- Data Engineers
- Banking and Finance Analysts
- Marketing Managers
- Supply Chain Professionals
- HR Managers
- Math, Science and Commerce Graduates
Life Sciences & Healthcare Analytics Course Module
360DigiTMG is offering Life Sciences and Healthcare Analytics courses in the USA. In the USA many innovations and discoveries are happening in the life sciences sector which is leading to novel treatments and drug discoveries. Massive investments are also involved to develop the Healthcare business and change the traditional process integrating data analytics tools. Life Sciences and Healthcare Analytics modules are comprehensively designed by prominent industry experts as per the latest business trends. The modules introduce the students to the exciting world of LSHC - the various sub-domains and the impact of Data Science. It also describes the advent of Big Data in Life Sciences and how that has changed the landscape. 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. The other modules of this course introduce EHR is electronic health records and other forms of data. Much emphasis will be given on the application of statistical tools Python and R and their importance in learning Data Analytics. Will learn the concepts of Deep Learning and Machine learning and can leverage Deep learning networks to analyze panoramic dental x-rays. Learn about Genomics, Proteomics, and Metabolics. Learn about Data modelling, predictive modelling, and clinical Natural language Processing. Through hands-on training, students will be able to learn the concepts and applications comprehensively. All the modules will be explained with real-time projects under the guidance of industry experts. Healthcare Analytics in the USA is emerging with advanced technologies, resourceful, and flexible work models that are going to attract the talent that has much potential to add more value to the business.
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.
Life Sciences & Healthcare Analytics Trends in USA
The US healthcare data analytics market is emerging at a rapid rate, as healthcare sectors are depending upon the IT-enabled solutions like business intelligence, data management, AI Machine learning, NLP, and automation to transform their clinical performance and operational agility. Let's have a look at the top technology trends that are impacting the life sciences industry. Life Sciences companies are focusing on Cloud-based technology to make data-driven decisions in Clinical research. Huge investments are being made in Drug Discovery and Research and development which are keen on adopting novel technologies like IoT, Augmented reality, and additive manufacturing. Life sciences companies are integrating advanced technologies like AI and Machine Learning into their DevOps for better outcomes, and monitor financial transactions and reinvest in automation.
Big Data Analytics plays a pivotal role in the Pharmaceutical sector. As a massive amount of data is generated in this sector, pioneers are anticipated to bring in the latest technologies to analyze the data and drive valuable insights that help in the discovery of many innovations. This will lead to better healthcare in the future. With the Data management approach, data of Life sciences transform the healthcare environment to a much better place. Treatment will be based on the probabilities and evidence delivered by data analysis. The novel tools and techniques are going to be implemented for productive decision making. This will facilitate the development of business in the healthcare sector and will sustain further. Life sciences practitioners with knowledge in data analytics skills are in great demand who can be taken into pharmaceutical sectors to draw insights from the clinical data.
How We Prepare You
Additional Assignments of over 60 hours
Live Free Webinars
Resume and LinkedIn Review Sessions
3 Month Access to LMS
Job Assistance in Data Science Fields
Unlimited Mock Interview and Quiz Session
Hands-on Experience in a Live Project
Life Time Free access to Industry Webinars
Call us Today!