Course Description

Course Learning Objectives: This course (18CS71) will enable students to:

1. Explain Artificial Intelligence and Machine Learning

2. Illustrate AI and ML algorithm and their use in appropriate applications

 Course Outcomes: The student will be able to :

1. Appaise the theory of Artificial intelligence and Machine Learning.

2. Illustrate the working of AI and ML Algorithms.

3. Demonstrate the applications of AI and ML.

Artificial Intelligence - Artificial intelligence (AI) is a field of computer science focused on creating systems that can perform tasks typically requiring human intelligence, such as problem-solving, reasoning, and learning. AI encompasses machine learning, neural networks, and deep learning to enable computers to analyze data, recognize patterns, and make autonomous decisions. Its applications range from virtual assistants and autonomous robots to medical diagnosis and language translation. 

Machine Learning -  Machine learning is a branch of artificial intelligence that focuses on developing algorithms that enable computers to learn from data and make predictions or decisions without being explicitly programmed. It encompasses various techniques, including supervised learning, unsupervised learning, and reinforcement learning, to extract patterns and insights from data. Machine learning applications are diverse, ranging from recommendation systems and image recognition to natural language processing and autonomous vehicles. To be effective, machine learning models require high-quality, labeled training data and continuous refinement to adapt to changing environments. Ethical considerations, bias mitigation, and transparency are crucial aspects of responsible machine learning development.

TEXT BOOKS

Download Text books by using below links.

Text Book -1 : Tom M Mitchell,“Machine Lerning”,1st Edition, McGraw Hill Education, 2017.

Text Book-2 : Elaine Rich, Kevin K and S B Nair, “Artificial Inteligence”, 3rd Edition, McGraw Hill Education, 2017.