Artificial Intelligence Full Course | Artificial Intelligence Tutorial for Beginners | Edureka

Introduction to AI and History00:00:11

An overview of Artificial Intelligence, its evolution from early concepts like Talos to modern breakthroughs such as the Turing Test, the birth of the term 'AI' in 1956, and major milestones like IBM Deep Blue and Watson.

Why AI is Important Now00:06:32

Discussion on why AI has gained prominence recently, driven by increased computational power (GPUs), the exponential growth of data, and significant advancements in neural network algorithms.

Real-world Applications of AI00:09:46

Examination of practical AI use cases, including Google's search predictions, JP Morgan's document analysis, healthcare diagnostics, Facebook's face verification, and Netflix's recommendation engines.

Types of AI and Programming Languages00:16:49

Explanation of the evolutionary stages of AI (Narrow, General, and Super Intelligence) and why Python is the preferred language for AI development due to its simplicity and extensive library support.

Machine Learning Fundamentals00:27:10

Defining Machine Learning as a subset of AI, covering the importance of data, the ML process (problem definition, data collection, cleaning, EDA, model building, and evaluation), and common terminology.

Types of Machine Learning00:48:58

Detailed breakdown of the three main types of machine learning: Supervised Learning (labeled data), Unsupervised Learning (unlabeled data and clustering), and Reinforcement Learning (trial and error).

Machine Learning Algorithms and Demos01:04:54

Technical walkthrough of core algorithms including Linear Regression, Logistic Regression, and Decision Trees, supported by practical Python demonstrations and model performance evaluation metrics like Mean Absolute Error.