Module 1:
Introduction to Artificial Intelligence
- Definition and concept of
Artificial Intelligence (AI)
- Historical development of AI
- Domains and applications of AI
- Real-world applications and
examples, current and future
Module 2: Machine
Learning
- Definition and types of Machine
Learning
- Machine Learning algorithms
(Supervised, Unsupervised, Reinforcement Learning)
- Practical application: Building a
Machine Learning application using Python
Module 3: Deep
Learning
- Introduction to Deep Learning and
its comparison with traditional Machine Learning
- Artificial Neural Networks (ANN)
and their applications
- Practical application: Creating a
simple neural network using TensorFlow and Keras
Module 4: Computer
Vision
- Definition, significance, and
applications of Computer Vision
- Image recognition and object
detection
- Practical application: Developing
an object detection application using OpenCV
Module 5: Natural Language Processing
- Introduction
to NLP and key techniques
- Text
analysis and sentiment analysis
- Practical
application: Building a sentiment analysis model using NLTK or spaCy
