Deep Learning Fundamentals for Healthcare
With Wuraola Oyewusi
Liked by 49 users
Duration: 2h 26m
Skill level: Intermediate
Released: 4/16/2025
Course details
Description
What is this course about?
Explore the exciting world of deep learning applications in healthcare through this in-depth course. Learn how to classify and detect abnormalities in X-ray images through convolutional neural networks (CNNs), fine-tuning pre-trained models, and leveraging zero-shot learning. Understand the basics of deep learning, including neural networks, model training, and hyperparameter tuning tailored specifically to healthcare. Engage in hands-on activities where you'll preprocess data, build models with Python, and utilize frameworks like TensorFlow and PyTorch. Develop practical skills in object detection and segmentation to diagnose and detect medical conditions effectively. Gain insights into ethical considerations and data limitations pertinent to applying AI in a medical context. By the end of this course, you will be equipped to apply deep learning techniques to real-world healthcare challenges, improving diagnostic accuracy and patient outcomes.Learning Objectives
What will I be able to do by the end of this course?
- Describe the intricacies of deep learning and how to implement it in a healthcare context.
- Use CNNs for image classification and diagnosis support, particularly focusing on X-ray analysis.
- Apply pretrained models and zero-shot learning techniques to healthcare data for innovative problem-solving.
- Describe data preprocessing and augmentation techniques in healthcare AI tasks.
- Evaluate the ethical implications and transparency issues associated with AI in healthcare decision-making.
Audience
Who is this course for?
- Healthcare professionals looking to develop AI competence in deep learning
- Machine learning practitioners specializing in healthcare data analytics
- Researchers and academics working with health-related data and innovation
Prerequisites
What do I need to know before taking this course?
- Basic understanding of machine learning principles and data science
- Familiarity with Python programming and basic statistical concepts
- Exposure to AI frameworks like TensorFlow or PyTorch is beneficial
Skills you’ll gain
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Meet the instructor
Learner reviews
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Diana Gaddam
Diana Gaddam
Product Owner | Bridging Business and Technology | Agile Leadership | Verification & Validation Engineer | SAFe®6.0 POPM | CSM® | ISTQB® CTAL-TA |…
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Contents
What’s included
- Practice while you learn 1 exercise file
- Learn on the go Access on tablet and phone
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