Certificate Course in
Life Sciences and HealthCare Analytics Program
- 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 Assistance
"Increased focus on value-based medicine has given ample growth opportunities to the life science industry. The life science analytics market is projected to reach $33 billion by 2024." - (Source). Healthcare analytics is emerging widely and is anticipated to transform the quality of healthcare organizations in the coming years. The adoption of electronic health records (EHR) will favor healthcare analytics to grow immensely. Many developed countries are using healthcare analytics as solutions to complex issues and for economic growth. Huge investments are being made by industry players in Research and development processes for exclusive solutions with unique features and gain a competitive edge in the healthcare market. Data Science and software developments will attain more profits in medicine than other technologies. IoT and Big data analytics will transform Healthcare and Malaysia is going to register $2.1billions by 2020.
Life Sciences and HealthCare
- Computer Skills
- Basic Mathematical Knowledge
- Analytical Mindsets
Healthcare Analytics Programme Overview
Healthcare Enterprises are leveraging AI-powered analytics for enhanced innovation and increased productivity. According to this PWC article, a little less than a third of the CEOs believe that AI will be the biggest disrupter to their industry. Following the trends in the broader Healthcare industry in the US, 360DigiTMG has developed the Certification Program in Healthcare Analytics. This course is meticulously designed to suit both Healthcare practitioners, IT Business Analysts and Data Scientists.
Healthcare Analytics Learning Outcomes
360DigiTMG offers the best training in Life Sciences and Healthcare Analytics by industrial experts. The Healthcare sector is developing rapidly with many innovations. There is a huge generation of data and it has to be analyzed for better insights. 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
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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 Modules
Advancement in Healthcare data analytics is bringing valuable insights for improving healthcare systems. The modules help the students to learn about different domains. Introduces data in electronic health records and other types of data like images from radiology, pathology, etc. Learn about the prime tools named Python, R, and its applications in analyzing healthcare data. Students will learn to decipher and assess designs of data models using Entity-Relationship (ER) diagrams. Understand about Genomics Exploratory Data Analysis, normalization, and batch effects of the data. Will be able to build MultiLayer Perceptron to build predictive analytic capabilities using the EHR and other clinical data. Learn to use CNN models to design prediction models that help to predict cancer using DICOM images. 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 modeling, predictive modeling, and clinical Natural language Processing. Through hands-on training, students will be able to learn the concepts and applications comprehensively. Real-time use cases and training by industrial experts help students to gain adequate knowledge and be able to overcome industrial challenges.
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.
Life Sciences and Healthcare Analytics Trends in Malaysia
Researchers have found that Malaysian people live longer with ill health, so the government is focussing to improve the better quality of life of Malaysians. Big data in health is playing a very promising role to give better insights for the doctors. Big data is the electronic health data sets that have massive data, by using advanced technologies healthcare organizations can exchange patients’ information, which leads to a proper diagnosis. IoT has a prominent effect in healthcare with benefits like remote monitoring, remote diagnosis, use of big data analytics, etc. This enables to predict incident rates of cardiac arrests, the prevalence of chronic diseases in patients. By the end of 2020, Telehealth will become a standard option as virtual consultation.
In the coming years, Telemedicine can solve the most challenging problems in the healthcare sector and a 5G wireless network will increase the potential of telehealth. Precision Medicine with data analytics will provide robust solutions based on patient populations and can predict successful treatment plans. Social Determinant data of healthcare (SDOH) will provide valuable inputs to improve the quality of care to hospitals. 45% of the US health systems and commercial organizations will depend on SDOH for business decisions, patients outreach, and risk assessments by the end of 2020. Artificial Intelligence and Machine learning will evolve incredibly in Healthcare, Artificial Intelligence will bring amazing results specifically in drug discovery, imaging diagnostics, and risk analytics applications.
How We Prepare You
Additional Assignments of over 60+ hours
Live Free Webinars
Resume and LinkedIn Review Sessions
Lifetime LMS Access
Job Assistance in Life Sciences and HealthCare Fields
Unlimited Mock Interview and Quiz Session
Hands-on Experience in Live Projects
Life Time Free Access to Industry Webinars
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Life Sciences Healthcare Panel of Coaches
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.
Sharat Chandra Kumar
- Areas of expertise: Data Science, 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.
- Areas of expertise: Data Science, 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 from 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.
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 Analytics Certificate is your passport to an accelerated career in LSHC industry.
FAQs for Life Sciences Healthcare Analytics Training
This course just assumes some basic computer familiarity and an analytical mindset. It definitely helps if the learner has some background in clinical bio-chemistry, 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 practice.
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 programme. 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 programme package.
Jobs in the Field of Life Sciences and HealthCare Analytics in Malaysia
Job titles available are Health care Analyst, Senior Analyst, Project Management Analyst, Data Analyst in healthcare domains.
Salaries in Malaysia for Life Sciences and HealthCare Analytics
The average salary at entry-level for Security Analyst in Malaysia will be RM 45,500, mid-career RM75,350, and for experienced it will increase. This varies according to the roles and responsibilities.
Life Sciences and HealthCare Analytics Projects in Malaysia
Many projects are being carried out in Clinical Data Analysis, Telemedicine, Drug discovery, diagnosis, Gene therapy, and so on.
Role of Open Source Tools in Life Sciences and HealthCare Analytics
Python, R, R studio and Jupyter are the open-source tools used to operate Healthcare Analytics.
Modes of Training in Life Sciences and HealthCare Analytics
360DigiTMG offers students the option of both classroom and online learning. We also support e-learning as part of our curriculum.
Industry Applications of Life Sciences and HealthCare Analytics in Malaysia
Healthcare Analytics has great potential in sectors like Hospitals, Research and Development, Insurance, Infrastructure, Pharmacy, and so on.