Arani Consulting

Email:info@araniconsulting.com

Part – A: Artificial Intelligence

Unit 1: Artificial Intelligence and Predicate Calculus

1. Introduction
2. AI Roots and Applications
3. Propositional Calculus
4. Predicate Calculus

Unit 2: AI Programming Languages

1. Prolog and Lisp
2. Syntax
3. Data Types
4. Control Mechanisms

Unit 3: Graph Theory and Strategies for State Space Searches

1. Graph Theory & Finite State Machine
2. State Space Search Algorithms
3. Reasoning Strategies

Unit 4: Heuristic Search Algorithms

1. Heuristic Search Issues
2. Heuristic Search Applications
3. Hill Climbing Algorithm
4. Dynamic Programming
5. Best-first Search

Unit 5: Control and Implementation of State Space Searches

1. Related Issues
2. Recursion-based Searching
3. Production and Blackboard Systems Architecture

Part – B: Artificial Intelligence

Unit 1: Introduction to Machine Learning

1. Introduction to Big Data and Machine Learning

Unit 2: Walking with Python or R

1. Understanding Python or R

Unit 3: Machine Learning Techniques

1. Types of Learning
2. Advice for Applying Machine Learning
3. Machine Learning System Design

Unit 4: Supervised Learning

1. Regression
2. Classification

Unit 5: Supervised Learning: Regression

1. Predicting House Prices: A Case Study in Regression

Unit 6: Supervised Learning – Clustering

1. Analyzing the Sentiment of Reviews: A Case Study in Classification

Unit 7: Unsupervised Learning

1. Clustering
2. Recommendation
3. Deep Learning

Unit 8: Unsupervised Learning Clustering

1. Document Retrieval: A Case Study in Clustering and Measuring Similarity

Unit 9: Unsupervised Recommendation

1. Recommending Products

Unit 10: Unsupervised Deep Learningb

1. Deep Learning: Searching for Images

Email:info@araniconsulting.com