Certified Artificial Intelligence Practitioner (CAIP) (AIP-210)

What you cover

4 modules

1. 01Understanding the Artificial Intelligence Problem
   • Describe how AI and machine learning solve business, government, public-interest and research problems
   • Analyze ML use cases and rank them by their probability of success
   • Research learning systems: image recognition, NLP, speech, recommendation, diagnostic and autonomous systems
   • Communicate with stakeholders
   • Identify potential ethical concerns
2. 02Engineering Features for Machine Learning
   • Recognize the impact of data quality and size on algorithms
   • Explain data collection and transformation in the ML workflow
   • Work with text, numerical, audio and video data
   • Transform numerical and categorical data
   • Address business risks and ethical concerns in feature engineering
3. 03Training and Tuning ML Systems and Models
   • Design machine and deep learning models
   • Optimize the algorithm: structure, run time and hyperparameters
   • Train, validate and test data subsets
   • Evaluate the model
   • Address business risks and ethical concerns in training and tuning
4. 04Operationalizing ML Models
   • Deploy a model
   • Secure and maintain a pipeline
   • Maintain the model in production
   • Address business risks and ethical concerns in operation