AI in Healthcare & Medical Imaging

What you'll learn

• Building and evaluating ML models
• Preparing data for training
• Tuning model performance
• Deploying models to production
• Understand working with Python libraries such as NumPy, pandas and scikit-learn
• Understand deploying and monitoring models

Planned outline shown above (sample metadata). The detailed module and lesson list for this course hasn't been published yet.

Description

Discover how AI is transforming healthcare. Build diagnostic models for medical imaging, disease prediction, and drug discovery using deep learning and clinical datasets.

What this course covers: AI in Healthcare & Medical Imaging works through working with Python libraries such as NumPy, pandas and scikit-learn, deploying and monitoring models, supervised and unsupervised learning and transformers and large language models.

Skills you will build: building and evaluating ML models, deploying models to production and preparing data for training.

Practical applications: prediction and classification systems, computer vision and NLP applications and AI features inside products.

Who should take this course: developers, data analysts and engineering students moving into machine learning and AI. It suits learners who already know the basics of machine learning and AI and want to go deeper.

Learning outcomes: by the end of the course you should be able to apply working with Python libraries such as NumPy, pandas and scikit-learn and building and evaluating ML models to your own work or projects, and know which areas to practise next.

Requirements

• Basic knowledge of machine learning and AI
• A computer with internet access
• Willingness to complete practice tasks

Your instructor

• P
  Priyanka S. ★★★★★ 4.5/5 Sample review

  I joined to get better at preparing data for training. The practical exercises on supervised and unsupervised learning were exactly what I needed. The hands-on notebooks made backpropagation finally make sense to me.

• N
  Nithya V. ★★★★★ 4.0/5 Sample review

  AI in Healthcare & Medical Imaging covered deploying and monitoring models in more depth than I expected. The pace was right for my level. The deployment section filled a gap most ML courses skip.

• A
  Aditya G. ★★★★★ 5.0/5 Sample review

  Good balance of theory and practice. The working with Python libraries such as NumPy, pandas and scikit-learn lessons helped me apply building and evaluating ML models in real situations. Loved that model evaluation got as much attention as model building.

Sample reviews are illustrative demo content, not verified purchases. Ratings from learners will appear here once submitted.