Life Sciences and HealthCare Analytics Program
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.
On-campus training in Malaysia: 16 hours
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. In accordance with 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 Data Analytics Learning Outcomes
Healthcare Analytics Course Modules
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.
The healthcare industry hit $3.5 Trillion in 2018 in USA alone and is projected to grow @ 5.5% from 2018-2022 according to CMS.GOV report. This PWC report says 25% of Healthcare industry CEOs say their organizations are using artificial intelligence in some form.
Block Your Time
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
Register for a free orientation
Healthcare Certification 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 Healthcare Predictive Analytics
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.
Heng Nguan Ting8 months ago
A company that give course from beginning level to advanced level. They will always keep in touch with their participant in order to get know about them and solve their problem accordingly. Nice place to start your learning.
Puteri ameena9 months ago
I joined the Data Science using R workshop and I really appreciated all the efforts that have been put into sharing the knowledge of Data Science. I learnt the reality of handling data unlike the theoretical classes we normally learn in university. I had so much fun too!! Thank you
Rong An Kiew9 months ago
I took part in the Jumpstart program 2018, I gained a lot of knowledge about Big Data from this program and there are also some experienced tutors teaching in this program. It provides some assignments to let us practise. Overall it is a good platform for learning Big Data.