Introduction to Artificial Intelligence in Healthcare

Learn the fundamentals of AI for clinical and operational use-cases with a practical, hands-on curriculum.

Duration

6 weeks

Level

Beginner – Intermediate

Effort

2–3 hrs/week

Prerequisites

Basic understanding of healthcare data recommended

Self-paced

Certificate coming soon

Understand the fundamentals of AI, ML, and DL in healthcare

Evaluate reproducibility, fairness, and ethics in AI

Apply NLP techniques to clinical data

Learn deployment strategies for real-world use

Course outline

Back to University

Introduction to Artificial Intelligence in Healthcare

Learn the fundamentals of AI for clinical and operational use-cases with a practical, hands-on curriculum.

Duration

6 weeks

Level

Beginner – Intermediate

Effort

2–3 hrs/week

Prerequisites

Basic understanding of healthcare data recommended

Self-paced

Certificate coming soon

Understand the fundamentals of AI, ML, and DL in healthcare

Evaluate reproducibility, fairness, and ethics in AI

Apply NLP techniques to clinical data

Learn deployment strategies for real-world use

Introduction to Artificial Intelligence in Healthcare

Course outline

Module 1. Foundations of AI in HealthcareBuild a clear understanding of what AI, ML, and DL are, and why they matter for modern healthcare.

Module 2. Core Concepts in Machine LearningExplore the principles of machine learning, how models are built, and their applications in healthcare.

Module 3. Deep Learning and Neural NetworksUnderstand the architecture of neural networks, deep learning, and how they are revolutionizing healthcare.

Module 4. Model Evaluation and ReproducibilityLearn how to measure, validate, and ensure the reliability of AI models in healthcare.

Module 5. Fairness, Bias, and Ethics in AIExplore the ethical challenges of AI, addressing bias, fairness, and the role of professionals in the AI age.

Module 6. Natural Language Processing (NLP) in HealthcareDiscover how NLP can unlock insights from clinical text and medical records for better patient outcomes.

Module 7. Deployment and Integration in HealthcareGain practical strategies to move from prototypes to real-world AI deployments in hospitals and clinics.

Introduction to Artificial Intelligence in Healthcare

Course outline

Module 1. Foundations of AI in HealthcareBuild a clear understanding of what AI, ML, and DL are, and why they matter for modern healthcare.

Module 2. Core Concepts in Machine LearningExplore the principles of machine learning, how models are built, and their applications in healthcare.

Module 3. Deep Learning and Neural NetworksUnderstand the architecture of neural networks, deep learning, and how they are revolutionizing healthcare.

Module 4. Model Evaluation and ReproducibilityLearn how to measure, validate, and ensure the reliability of AI models in healthcare.

Module 5. Fairness, Bias, and Ethics in AIExplore the ethical challenges of AI, addressing bias, fairness, and the role of professionals in the AI age.

Module 6. Natural Language Processing (NLP) in HealthcareDiscover how NLP can unlock insights from clinical text and medical records for better patient outcomes.

Module 7. Deployment and Integration in HealthcareGain practical strategies to move from prototypes to real-world AI deployments in hospitals and clinics.