Online/ e-LMS
Self Paced
Moderate
8 Weeks
About
This course is meticulously designed to provide healthcare professionals with an in-depth understanding of artificial intelligence (AI) and machine learning (ML) applications in the healthcare and clinical analytics sector.
Aim
This course focuses on leveraging AI to analyze healthcare data effectively, improve diagnostics, optimize treatment planning, and enhance public health insights.
Program Objectives
- Equip participants with foundational knowledge of AI and ML technologies in healthcare analytics.
- Explore predictive modeling, natural language processing (NLP), and their applications in clinical documentation and patient care.
- Address the ethical considerations and privacy laws relevant to deploying AI solutions in healthcare settings.
- Combine theoretical knowledge with practical applications through case studies and a capstone project.
Program Structure
MODULE 1 : Introduction to Healthcare Analytics
- Overview of healthcare analytics.
- Data types and sources in healthcare.
- Introduction to health informatics.
- Key challenges and opportunities in healthcare data analysis.
MODULE 2 : Fundamentals of AI and Machine Learning
- Basics of artificial intelligence.
- Introduction to machine learning and deep learning.
- Supervised vs. unsupervised learning in healthcare.
- Tools and technologies for AI development (Python, TensorFlow, etc.).
MODULE 3 : Predictive Modeling in Healthcare
- Understanding predictive analytics in healthcare.
- Techniques for disease outbreak prediction.
- Patient risk stratification models.
- Machine learning algorithms for healthcare predictions.
MODULE 4 : Natural Language Processing for Clinical Documentation
- Introduction to NLP and its applications in healthcare.
- Text mining and analysis of clinical notes.
- Sentiment analysis for patient feedback.
- Implementing NLP projects using Python and NLTK.
MODULE 5 : Data Ethics and Privacy in Healthcare
- Ethical considerations in AI applications.
- Data privacy laws and regulations (HIPAA, GDPR).
- Ensuring fairness and avoiding bias in AI models.
- Case studies on ethical dilemmas in healthcare analytics.
Program Outcomes
- Proficiency in applying AI and ML techniques to healthcare data for improved analytics and insights.
- Ability to implement predictive models and NLP to enhance clinical documentation and patient care strategies.
- Understanding of the ethical, legal, and privacy considerations in using AI in healthcare.
- Hands-on experience with a capstone project that mirrors real-world challenges in healthcare analytics.
- Preparedness for roles that require the integration of AI into healthcare operations, aiming to innovate and improve healthcare outcomes through technology.
Fee Structure
Standard Fee: INR 10,998 USD 198
Discounted Fee: INR 5499 USD 99
We are excited to announce that we now accept payments in over 20 global currencies, in addition to USD. Check out our list to see if your preferred currency is supported. Enjoy the convenience and flexibility of paying in your local currency!
List of CurrenciesBatches
Live
Certificate
Program Assessment
Certification to this program will be based on the evaluation of following assignment (s)/ examinations:
| Exam | Weightage |
|---|---|
| Mid Term Assignments | 50 % |
| Project Report Submission (Includes Mandatory Paper Publication) | 50 % |
To study the printed/online course material, submit and clear, the mid term assignments, project work/research study (in completion of project work/research study, a final report must be submitted) and the online examination, you are allotted a 1-month period. You will be awarded a certificate, only after successful completion/ and clearance of all the aforesaid assignment(s) and examinations.
Program Deliverables
- Access to e-LMS
- Real Time Project for Dissertation
- Project Guidance
- Paper Publication Opportunity
- Self Assessment
- Final Examination
- e-Certification
- e-Marksheet
Job Opportunities
- Healthcare Data Analyst
- Clinical Data Scientist
- Health Informatics Specialist
- AI Implementation Specialist in Healthcare
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Recent Feedbacks In Other Workshops
The course was well communicated and interactive
lecture delivered well but the title of workshop was a little misleading
