Artificial Intelligence
Indian Institute of Information Technology Dharwad
Data Science and Intelligent Systems
Course: Algorithms and Artificial Intelligence
Course Code: DS206 Credit: 4 (L3-T1-P0-S0-T4) Total Hrs:52
Overview: This is a course to understand, learn, and test various available algorithms to perform Artificial Intelligence (AI) in real world projects and systems.
Course Objectives:
● To understand the importance of artificial intelligence of systems using various algorithms.
● To use intelligent algorithms for solving problems, which are related to the real-world or IT industry.
● To extend the use of AI to the extent of other domains and fields.
https://github.com/animesh88/Artificial_Intelligence_Course
Basic Artificial Intelligence
1.1 History and Definitions of AI
1.3 Deterministic, Non-Deterministic, Optimization, Approximation, and Probabilistic
1.4 Probabilistic Fermat's Primality test and Deterministic Primes in P (AKS algorithm)
Classical Artificial Intelligence
2.1 Agents, States, and Environments
2.2 Logical AI First-order and Propositional logics
2.3 Decision Tree Learning and Decision Theory
2.4 State Space search, Uninformed search, Informed search, Heuristics
2.5 Constraint satisfaction problems (CSPs)
Modern Artificial Intelligence
3.1 Knowledge Representation and Reasoning
3.2 Data Science, Knowledge Discovery, and Big Data Analytics - Systems
3.3 No-SQL, ACID Property, CAPs Theorem, and When to use No-SQL in comparison to SQL
Project: Choose one or more AI algorithms and apply them on real-world applications. Conduct and demonstrate experiments to report the findings and observations.
Books:
Stuart Russel, and Peter Norvig. "Artificial intelligence: A modern approach. third edit." Upper Saddle River, New Jersey 7458 (2010).
Kevin Knight, Elaine Rich, Shivashankar B. Nair, Artificial Intelligence Third Edition
Course outcome:
CO1. Write intelligent algorithms using existing theories and knowledge.
CO2. Learning artificial intelligence skills to use, create, and develop systems.
CO3. Test, evaluate, and assess a project's capability to behave without human intervention.
CO4. Implementing a part of a project based on the intelligent algorithms.
CO5. Applying the learned theories and algorithms for real world applications, projects, and systems.
Evaluation Method
Item, Weightage (%)
Assignment 1 Write-up of the project: 10
Project Technical work: 20
Assignment 2 Presentation of Project: 10
Quiz or Viva: 10
Mid Term: 20
End Term: 30
Prepared by: Dr. Animesh Chaturvedi