This Artificial Intelligence full course from Edureka is designed for beginners who want to build a strong foundation in AI, machine learning, and deep learning. The course provides a complete structured learning path starting from basic concepts and progressing to advanced AI techniques used in real-world systems.

The course begins with an introduction to artificial intelligence, its history, and its growing demand in modern industries. It explains what AI is and how it is applied in different fields such as healthcare, finance, automation, and technology systems.

Students will then explore machine learning in depth, including supervised, unsupervised, and reinforcement learning. The course explains the full machine learning workflow and introduces key algorithms such as linear regression, logistic regression, decision trees, random forests, Naive Bayes, KNN, and SVM.

A major section of the course focuses on unsupervised learning techniques like clustering and reinforcement learning concepts. Learners also gain hands-on understanding of how these models are trained and applied.

The course then moves into deep learning, explaining neural networks including perceptrons, multi-layer networks, backpropagation, CNNs, and RNNs. It also introduces natural language processing (NLP) and how machines understand and process human language.

By the end of this course, learners will have a complete understanding of artificial intelligence, machine learning algorithms, deep learning models, and NLP applications, along with how these technologies are used in real-world AI systems.