Certified Artificial Intelligence (AI) Practitioner (CN8534)

Module 1: Solving Business Problems Using AI and ML

• Identify AI and ML Solutions for Business Problems
• Formulate a Machine Learning Problem
• Select Appropriate Tools

Module 2: Collecting and Refining the Dataset

• Collect the Dataset
• Analyze the Dataset to Gain Insights
• Use Visualizations to Analyze Data
• Prepare Data

Module 3: Setting Up and Training a Model

• Set Up a Machine Learning Model
• Train the Model

Module 4: Finalizing a Model

• Translate Results into Business Actions
• Incorporate a Model into a Long-Term Business Solution

Module 5: Building Linear Regression Models

• Build a Regression Model Using Linear Algebra
• Build a Regularized Regression Model Using Linear Algebra
• Build an Iterative Linear Regression Model

Module 6: Building Classification Models

• Train Binary Classification Models
• Train Multi-Class Classification Models
• Evaluate Classification Models
• Tune Classification Models

Module 7: Building Clustering Models

• Build k-Means Clustering Models
• Build Hierarchical Clustering Models

Module 8: Building Advanced Models

• Build Decision Tree Models
• Build Random Forest Models

Module 9: Building Support-Vector Machines

• Build SVM Models for Classification
• Build SVM Models for Regression

Module 10: Building Artificial Neural Networks

• Build Multi-Layer Perceptrons (MLP)
• Build Convolutional Neural Networks (CNN)

Module 11: Promoting Data Privacy and Ethical Practices

• Protect Data Privacy
• Promote Ethical Practices
• Establish Data Privacy and Ethics Policies