Artificial Intelligence in Industrial and Management Engineering

Overview

ABOUT THE COURSE:

Artificial intelligence is actively enabling novel solutions in industrial and management sectors. This results in a significant increase in the demand for specialists who comprehend the principles underlying the technological systems that propel contemporary businesses.

This course presents the foundational principles of many subdomains of artificial intelligence along with their applications. The course aims to serve as an introductory platform for students to explore artificial intelligence approaches.

The course employs the Python programming language to illustrate and impart theoretical topics. The course motivates students to explore the diverse subdomains of AI according to their personal interests by offering ample resources at each stage.INTENDED AUDIENCE:

Students of all Engineering and Science disciplines.PREREQUISITES:

The student should have completed two semesters of UG Engineering or Science program.INDUSTRY SUPPORT:

TCS, Accenture, Tech Mahindra, Capgemini India Pvt Ltd., Genpact.

Syllabus

• Introduction to Artificial Intelligence
Definition and history of AI
Importance of AI in industrial and management sectors
Overview of subdomains in AI
• Programming with Python for AI
Basics of Python programming
Libraries and tools important for AI (NumPy, Pandas, Matplotlib, Scikit-learn)
• Machine Learning Fundamentals
Supervised vs Unsupervised learning
Key algorithms: Linear Regression, Decision Trees, k-Means
Applications in industry and management
• Data Collection and Preprocessing
Data sources and data quality
Preprocessing techniques (normalization, standardization, encoding)
• Neural Networks and Deep Learning
Fundamentals of neural networks
Introduction to deep learning
Use cases in industry
• Natural Language Processing (NLP)
Basics of NLP
Tools and techniques (tokenization, sentiment analysis)
Applications in management
• Robotics and Automation
Principles of robotics in industrial settings
Automation tools and techniques
Case studies
• AI in Decision Making and Optimization
Role of AI in enhancing decision-making processes
Optimization algorithms (Genetic Algorithms, Particle Swarm Optimization)
Real-world applications
• Ethical and Social Implications of AI
Understanding biases in AI
AI ethics and data privacy
Case studies on AI ethics
• Capstone Project
Integration of learned concepts into a practical project
Aligning the project with real-world industrial or management challenges
• Resources and Further Exploration
Recommended books, articles, and online courses
Overview of career opportunities in AI-related fields
• Industry Engagement
Guest lectures from industry partners (TCS, Accenture, etc.)
Case studies and real-world applications from partner industries

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Taught by

Prof. Deepu Philip, Prof. Prabal Pratap Singh

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Subjects

Computer Science