Certificate Course in
Life Sciences and HealthCare Analytics Course in USA
- Get Trained by Trainers from ISB, IIT & IIM
- 16 Hours of Interactive Online Sessions
- 20 Hours of Free Python Programming Videos
- Job Placement Assistance
- Authorised by National Educational Alliance for Technology - NEAT
2167 Learners
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
Total Duration
1 Month
Prerequisites
- 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 Outcome
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.
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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 & Healthcare Analytics Course Module
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.
- Challenges and Opportunities in Life Sciences and Healthcare Analytics
- Overview of AI Applications in Life Sciences and Healthcare
In this module we will be discussing the CRISP-ML (Q), it is a research methodology used in the life sciences to integrate statistical and machine learning methods with clinical reasoning in order to improve the accuracy of medical diagnoses and treatments. The goal of CRISP-MLQ is to develop quantitative models that can assist healthcare professionals in making more informed and efficient decisions, while also taking into account the uncertainties and biases inherent in medical data.
This module covers the essentials of Exploratory Data Analysis (EDA) and Data Preprocessing in the context of Life Sciences and Healthcare data. The goal is to familiarize participants with techniques for cleaning, transforming, and preparing data for analysis in order to obtain meaningful insights and inform decision making.
This module explores the application of K-means algorithm, a popular unsupervised learning technique, in the Life Sciences and Healthcare domain. Participants will learn how to use K-means for data clustering, gain hands-on experience in implementing the algorithm, and understand its potential for solving real-world problems in the field.
This module focuses on the K-Nearest Neighbors (KNN) algorithm, a popular supervised learning method. The module covers how KNN works, its implementation in the Life Sciences and Healthcare domain, and its applications for solving various problems in the field, such as diagnosis and prognosis. Participants will gain hands-on experience in using KNN algorithms for data analysis and prediction
In this module, the working principle of Decision Tree algorithms for supervised learning in Life Sciences and Healthcare is explored, with a focus on TNBC relapse prediction. Participants will gain a thorough understanding of how Decision Trees operate and their practical applications, through hands-on work with a real-world TNBC relapse prediction use case
This module focuses on the working principle and application of Linear Regression, a supervised learning technique, in Life Sciences and Healthcare. A simple use case of predicting Adipose tissue using waist circumference is used to demonstrate the implementation and potential of Linear Regression in the field. Participants will gain hands-on experience in using Linear Regression for data analysis and prediction.
This module discusses the usage of Multilayer Perceptrons (MLP) in Life Sciences and healthcare, through the exploration of a practical use case. Participants will learn about MLP, its working principle, and how it can be applied to solve real-world problems in the field, and gain hands-on experience in using MLP for data analysis and prediction.
This module examines the application of Natural Language Processing (NLP) in Life Sciences and Healthcare, using the use case of sentiment analysis on drugs. Participants will learn about NLP, its potential and challenges in the field, and gain hands-on experience in using NLP techniques for sentiment analysis on drug-related data.
Tools Covered
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.
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Resume and
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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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Alumni Speak
"The training was organised properly, and our instructor was extremely conceptually sound. I enjoyed the interview preparation, and 360DigiTMG is to credit for my successful placement.”
Pavan Satya
Senior Software Engineer
"Although data sciences is a complex field, the course made it seem quite straightforward to me. This course's readings and tests were fantastic. This teacher was really beneficial. This university offers a wealth of information."
Chetan Reddy
Data Scientist
"The course's material and infrastructure are reliable. The majority of the time, they keep an eye on us. They actually assisted me in getting a job. I appreciated their help with placement. Excellent institution.”
Santosh Kumar
Business Intelligence Analyst
"Numerous advantages of the course. Thank you especially to my mentors. It feels wonderful to finally get to work.”
Kadar Nagole
Data Scientist
"Excellent team and a good atmosphere. They truly did lead the way for me right away. My mentors are wonderful. The training materials are top-notch.”
Gowtham R
Data Engineer
"The instructors improved the sessions' interactivity and communicated well. The course has been fantastic.”
Wan Muhamad Taufik
Associate Data Scientist
"The instructors went above and beyond to allay our fears. They assigned us an enormous amount of work, including one very difficult live project. great location for studying.”
Venu Panjarla
AVP Technology
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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.
Jobs in the field of Life Sciences and HealthCare Analytics in USA
Job titles available are Health care Analyst, Senior Analyst, Project Management Analyst, Data Analyst in healthcare domains.
Salaries for Life Sciences and HealthCare Analytics Professionals
The average salary for Healthcare Analysts in the USA at an early level is $67,363 and at the mid-career level, the average salary is $71,036 approximately.
Life Sciences and HealthCare Course Projects
The life sciences industry is always on a constant drive with advanced research and development. Latest innovations in drug discovery, Gene therapy, huge investments in drug launches, and discoveries like telemedicine, Healthcare apps, etc.
Role of Open Source Tools in Life Science and HealthCare Analytics
Python, R, R studio, and Jupyter are the open-source tools that are essential for learning Healthcare Analytics.
Modes of Training of Healthcare Analytics Course
360DigiTMG offers students the option of both classroom and online learning. We also support e-learning as part of our curriculum. 1:1 individual mentorship is provided to the students to guide them throughout the course.
Industry Application of Life Science and HealthCare Analytics Course
Healthcare Analytics is gaining popularity and has great potential in sectors like Hospitals, Research and Development, Drug discovery, Biomedicine, Pharmacy, Insurance, and so on.
Companies That Trust Us
360DigiTMG offers customised corporate training programmes that suit the industry-specific needs of each company. Engage with us to design continuous learning programmes and skill development roadmaps for your employees. Together, let’s create a future-ready workforce that will enhance the competitiveness of your business.
Student Voices