Introduction to AI & ML

This program provides a foundational understanding of Artificial Intelligence and Machine Learning, focusing on how intelligent systems are built and applied in real-world scenarios. It is designed for beginners to understand core concepts, workflows, and practical applications of AI and ML technologies.

Fundamentals of AI & ML

• What is Artificial Intelligence and Machine Learning

• Difference between AI, ML, and Deep Learning

• Types of machine learning systems

• AI applications in everyday life

• Overview of AI development lifecycle

Data and Machine Learning Basics

• Role of data in machine learning

• Types of datasets and features

• Data preprocessing fundamentals

• Training and testing data concepts

• Importance of data quality

Core Machine Learning Concepts

• Supervised vs unsupervised learning

• Regression and classification basics

• Clustering and pattern recognition

• Model training concepts

• Evaluation and accuracy measurement

Introduction to AI Models

• Basic machine learning algorithms

• Overview of decision trees and linear models

• Concept of neural networks

• Model performance improvement

• Real-world model applications

AI Use Cases and Applications

• AI in business and industry

• Healthcare, finance, and retail applications

• Predictive analytics use cases

• Automation and intelligent systems

• Future trends in AI adoption