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Certification

Certification: Build and Evaluate Medical AI Models with TensorFlow

Show you know how to use AI—gain hands-on experience developing and evaluating medical AI models with TensorFlow. Enhance your expertise and demonstrate your skills in one of healthcare’s most in-demand technology areas.

Exam of 10 to 20 questionsCertificate for LinkedInIntermediate · Expert · Technical
IT and developmentDeepSeek
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The exam

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Multiple-choice questions about the course. Pass with 70% or more and your certificate is issued at once, with a public page and an "Add to LinkedIn" button.

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What the exam covers

2 questions from each of the 10 chapters of the course

20 multiple-choice questions, drawn fresh for every attempt. Pass with 70% or more.

  1. 01Intro and Google Colab1:50
  2. 02Facts about chest X-rays4:46
  3. 03Defining a problem5:57
  4. 04Preparing the data7:12
  5. 05Training the model12:15
  6. 06Running the model5:05
  7. 07Evaluating performance11:39
  8. 08Histogram, sensitivity and specificity12:16
  9. 09AUC curve7:19
  10. 10Saving the model1:28
About the course

The Certification: Build and Evaluate Medical AI Models with TensorFlow equips you to develop and assess advanced AI solutions for healthcare using industry-leading tools. Gain expertise in practical implementation, clinical model evaluation, and adapt to future challenges in medical technology for a future-proof career. Enroll now to unlock higher income potential and harness the power of AI in medicine.

This certification covers the following topics:

  • The Potential of Machine Learning in Healthcare
  • Practical Implementation with TensorFlow
  • Importance of Model Evaluation in a Clinical Context
  • Working with Medical Imaging Data
  • The Process of Data Preparation
  • Understanding and Mitigating Data Imbalance
  • Evaluation Metrics: Accuracy, Sensitivity, Specificity, and AUC
  • Visualisation and Interpretation of Model Performance
  • The Significance of Choosing an Appropriate Decision Threshold
  • Model Saving and Deployment
  • Real-World Application: Detecting Cardiomegaly
  • Transfer Learning and Data Augmentation in Medical AI
  • Ethical Implications of Using AI for Medical Diagnosis
  • Integrating AI Models into Clinical Workflows

Jobs this certification suits

Our AI checked this certification against 500 jobs; these get the most out of it. Each job links to its learning path.

Biomedical Engineers