Enroll Now
Edit Content
Contact Information

Reach out to us and let's discuss your unique digital vision.

Connect with DHI Digital and let’s turn your digital vision into reality with expert strategies and innovative solutions.

Head Office

Jawalakhel, Lalitpur, Nepal

Telephone

+977 9856064310
+977 9851205215

Email Address

info@dhidigital.com

Open Hours

Sun - Frid 10AM - 5PM

Course- Data Science

Data Science for the
Medical Sector

Leverage Data Science & AI to Transform Healthcare

Course Duration: 60 Days
Course Pricing: RS 35000
Course Model : Online/Offline

Course Overview

Unlock the power of data science, machine learning, and AI in healthcare with this specialized Data Science for the Medical Sector course. Learn how to analyze medical data, predict diseases, optimize hospital operations, and leverage AI for medical imaging, genomics, and electronic health records (EHRs). This hands-on course covers Python, Pandas, NumPy, Scikit-Learn, TensorFlow, and NLP to equip you with in-demand healthcare analytics skills.

Who is This Course For?

  • Healthcare Professionals & Medical Researchers
  • Data Scientists & Analysts Interested in Healthcare
  • Bioinformatics & Genomics Researchers
  • AI & Machine Learning Enthusiasts in Medicine
  • Students & Professionals in Public Health & Hospital Management

Why Enroll in This Course?

  • High Demand in Healthcare AI – Data-driven healthcare is revolutionizing patient care.
  • Analyze & Predict Medical Data – Work with real-world medical datasets.
  • Machine Learning for Medicine – Learn predictive analytics for diagnosis and treatment.
  • Medical Imaging & AI – Apply deep learning to radiology and pathology.
  • No Prior Data Science Experience Needed – Beginner-friendly with step-by-step guidance.
  • Industry-Relevant Skills – Prepare for careers in healthcare analytics and AI research.

What You Will Learn

  • Python for Medical Data Analysis – Process and analyze medical datasets.
  • Exploratory Data Analysis (EDA) in Healthcare – Identify trends in patient data.
  • Machine Learning for Disease Prediction – Diagnose diseases using AI.
  • Medical Imaging & Deep Learning – Apply AI to radiology, pathology, and MRI scans.
  • Healthcare Data Ethics & Compliance – Ensure HIPAA & GDPR compliance.
  • AI Applications in Drug Discovery & Genomics – Use ML in personalized medicine.

Course Outcome

  • Work on real-world healthcare datasets
  • Master Python, Pandas, NumPy, and AI for medicine
  • Analyze EHRs, medical images, and genomic data
  • Develop predictive models for disease diagnosis
  • Learn healthcare data privacy and AI ethics
  • Certification upon completion

Tools & Software Covered

  • Python & Jupyter Notebook – Programming & Data Analysis
  • Pandas & NumPy – Data Manipulation & Processing
  • Matplotlib & Seaborn – Data Visualization & Graphing
  • Scikit-Learn & TensorFlow – Machine Learning & AI
  • DICOM & OpenCV – Medical Imaging & Analysis
  • NLTK & SpaCy – Natural Language Processing in Healthcare

Lessons:

  1. Overview of Data Science & AI in Medicine
  2. Understanding Healthcare Data Types (EHRs, Clinical Trials, Genomics)
  3. Setting Up Python & Jupyter Notebook for Medical Data Science
  4. Introduction to Medical Data Libraries – Pandas, NumPy, Matplotlib
  5. Challenges & Opportunities in Healthcare Data Science
  1. Importing & Cleaning Medical Datasets (CSV, Excel, DICOM)
  2. Handling Missing Data & Outliers in Patient Records
  3. Data Wrangling for Electronic Health Records (EHRs)
  4. Visualizing Medical Trends with Seaborn & Matplotlib
  5. Feature Engineering for Disease Prediction
  1. Introduction to Supervised & Unsupervised Learning in Healthcare
  2. Building Regression Models for Patient Risk Assessment
  3. Decision Trees & Random Forest for Diagnosing Diseases
  4. Implementing Support Vector Machines (SVMs) for Medical Classification
  5. Evaluating Model Accuracy & ROC Curves
  1. Basics of Neural Networks for Medical AI
  2. Convolutional Neural Networks (CNNs) for Image Analysis
  3. Applying AI to X-ray, MRI, and CT Scan Classification
  4. Object Detection in Pathology & Radiology Images
  5. Using Transfer Learning for Medical AI Applications
  1. Introduction to NLP in Healthcare
  2. Text Mining in Medical Research & Clinical Notes
  3. Sentiment Analysis in Patient Feedback & Reports
  4. Named Entity Recognition (NER) for Drug & Disease Identification
  5. AI Chatbots for Healthcare Support
  1. Introduction to Genomics & Data Science Applications
  2. Processing DNA & RNA Sequences with Python
  3. Machine Learning in Drug Discovery & Personalized Medicine
  4. Clustering & Classification in Genetic Data
  5. Ethical Considerations in AI-Driven Medicine
  1. Introduction to Healthcare Data Privacy Laws (HIPAA, GDPR)
  2. Data Encryption & Security in Medical AI Systems
  3. Handling Patient Data Anonymization
  4. AI Bias & Fairness in Medical Applications
  5. Ethical Challenges in AI-Powered Healthcare
  1. Case Studies – AI in Cancer Detection, COVID-19 Predictions, & More
  2. Integrating AI with Hospital Management Systems
  3. Cloud-Based Medical AI & IoT Applications
  4. Building a Portfolio for Healthcare Data Science Jobs
  5. Future Trends in AI & Data Science for Medicine

Unlock Access To The Orientation Class

Fill out this form to unlock access to the Orientation Class. Your information will help us schedule the class at a time that’s convenient for most participants.

* The data you provide will be kept confidential and will not be shared with anyone.

Frequently Asked Questions (FAQ) – Data Science for the Medical Sector

1. Who is this course for?

This course is designed for healthcare professionals, medical researchers, data analysts, AI enthusiasts, and students who want to apply data science in the medical field. No prior coding experience is required.

2. Do I need programming skills to take this course?

No, this course is beginner-friendly. We will start with the basics of Python and gradually introduce data science and AI concepts.

3. What will I learn in this course?

You will learn Python, Pandas, NumPy, Scikit-Learn, machine learning, medical imaging analysis, EHR data processing, bioinformatics, and AI applications in healthcare.

4. What tools and software will be used?

You will work with Python, Jupyter Notebook, Pandas, NumPy, Scikit-Learn, TensorFlow, OpenCV, and NLP tools for healthcare data analysis.

5. Will I receive a certificate after completing the course?

Yes! You will receive a certification upon successful completion, which can enhance your career in medical data science.

©2025 Dhi Digital Pvt. Ltd. All Rights Reserved.

Enroll Now & Upgrade Your Skills!

Choose your preferred learning mode.
Choose your preferred learning shift.
How did you hear about us?