Artificial Intelligence
Complete Healthcare Artificial Intelligence Course
Healthcare Artificial Intelligence.
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Included with Skilldacity Membership
About This Course
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Healthcare Artificial Intelligence. Create powerful AI models for real-world healthcare applications using Data Science, Machine Learning, and Deep Learning. This course empowers learners to design, build, and deploy AI-driven healthcare solutions using modern data science and machine learning tools.
Whether you are a beginner or an experienced professional looking to transition into healthcare AI, this course provides a hands-on, end-to-end understanding of how intelligent systems can transform patient outcomes, diagnostics, and medical research. You’ll learn the core mathematical foundations, coding techniques, and algorithmic design patterns behind state-of-the-art AI systems—while building practical models that address real healthcare challenges such as disease prediction, diagnosis support, and treatment optimization.
What You’ll Learn
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Core Python and Data Science Tools: Pandas, Seaborn, Matplotlib, and Anaconda for data analysis and visualization.
Deep Learning and Neural Networks: Artificial Neural Networks (ANNs), Keras, Google Colab, Jupyter Notebook, and Deep Feedforward Networks.
Activation Functions: Sigmoid, Tanh, ReLU, Leaky ReLU, Exponential Linear Unit (ELU), and Swish functions.
Machine Learning Algorithms: Logistic Regression, Naive Bayes, Support Vector Machines (SVM), K-Nearest Neighbors (KNN), Random Forest, and Markov Models.
Advanced Model Techniques: Stacking models, Maximum Voting Classifiers, Response Encoding, and One-Hot Encoding.
Data Preprocessing: Data cleaning, handling missing values, normalization, feature scaling, temporal and geolocation feature extraction, and data standardization.
Exploratory Data Analysis: Data visualization, geolocation mapping, anomaly detection, and correlation studies.
Model Evaluation: Confusion Matrix, ROC Curve, and accuracy testing.
Natural Language Processing (NLP): Using NLTK (Natural Language Toolkit) for healthcare text and response data analysis.
AI in Healthcare Applications: Building classification models for medical diagnostics, disease prediction, and healthcare optimization.
Hands-on Healthcare Projects
You’ll apply what you learn through real-world, project-based learning, building your own models and solutions for actual healthcare problems.
Projects include:
DNA Classification Project
Heart Disease Classification Project
Coronary Artery Disease Diagnosis
Breast Cancer Detection
Diabetes Prediction with Multilayer Perceptrons
Predicting Taxi Fares in New York City
Iris Flower Classification
Medical Treatment Recommendation Project
Skills You’ll Gain
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Developer
Data Science
Machine Learning
Database
Artificial Intelligence
Career Path
Artificial Intelligence
Provider
Skilldacity
Level
Foundational
Certification
No certification associated
Access
Included with eligible Skilldacity subscription
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