AI & Machine Learning :  Practical Implementation & Automation

Target Group

Business professionals and managers seeking to understand AI applications
IT staff and analysts aiming to automate data processes
New entrants and fresh graduates interested in digital and AI careers

Course Objectives

1. Understand basic AI and ML concepts

2. Differentiate between types of machine learning models

3. Apply no-code/low-code platforms for ML tasks

4. Interpret AI outputs for decision-making

5. Explore use cases in business and industry

6. Plan basic AI readiness for implementation
   
   

Course Learning Outcomes (CLOs)

1. Explain core concepts of AI and machine learning

2. Differentiate between supervised, unsupervised, and reinforcement learning

3. Use a no-code or low-code tool to create and train a model

4. Interpret the results of ML models using simple metrics

5. Identify relevant AI applications for various business functions

6. Assess the data and resources needed to start an AI project