Overview
Explore the fundamentals of artificial intelligence in industrial and management contexts, learning Python-based applications across various AI subdomains including knowledge representation, expert systems, and machine learning.
Syllabus
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- 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
Taught by
Prof. Deepu Philip, Prof. Prabal Pratap Singh
Tags
On-Demand
