Why this course?

Description

This Artificial Intelligence Internship module offers a hands-on journey through foundational AI concepts, machine learning, deep learning, computer vision, and real-world applications. Designed for beginners, the 20+ day program introduces Python basics, AI models, CNNs, and NLP techniques through structured projects and assignments.

Python and progress through supervised machine learning models, natural language processing, deep learning networks, and advanced computer vision tasks. Each day includes practical presentations, datasets, source code, and quizzes to reinforce understanding. From fake news detection to fingerprint authentication, the internship provides an end-to-end AI exposure with projects, source code, and real datasets.

Day-Wise Breakdown:

Day 1: Introduction of Artificial Intelligence

• Presentation: Introduction to AI

Day 2: Python Setup and Basics

• Topics: Installing Python, Python libraries, and basic programming
• Resources: Colab files, starter datasets

Day 3: Overview of AI

• Presentation: AI Concepts and Use Cases (Tamil)

Day 4: Training & Testing ML Models

• Focus: Music dataset model training
• Resources: Colab files, music dataset

Day 5: Predicting Weight Using Features

• Project: Predict weight based on height and gender
• Resources: Dataset, source code

Day 6: Introduction to Natural Language Processing (NLP)

• Presentation: Basics of NLP

Day 7: Fake News Detection using NLP

• Project: Text classification for fake news
• Resources: Dataset, source code, presentation

Day 8: Language Translator

• Focus: Building text and speech language translators
• Resources: Source code, presentation

Day 9: Introduction to Deep Learning

• Presentation: Concepts of Deep Learning

Day 10: Neural Network Design

• Project: Build and train a neural network for diabetes prediction
• Resources: Dataset, source code, presentation

Day 11: Image Classification using CNN

• Project: Image classification with convolutional neural networks
• Resources: Dataset, source code, presentation

Day 12: Leaf Disease Detection with CNN

• Project: Detect plant leaf diseases from images
• Resources: Dataset, source code

Day 13: Traffic Sign Detection

• Project: Classify traffic signs using deep learning
• Resources: Dataset, source code

Day 14: Fingerprint Authentication

• Project: Fingerprint-based identity authentication
• Resources: Dataset, source code, presentation

Day 15: Introduction to Computer Vision

• Presentation: Overview of CV and image processing examples

Day 16: Face Recognition using OpenCV

• Project: Implement face detection and recognition
• Resources: Dataset, source code, presentation

Day 17: Age and Gender Detection

• Project: Predict gender and age from facial features
• Resources: Dataset, source code, presentation

Day 18: Image Classification using KNN

• Project: Use K-Nearest Neighbors for image recognition
• Resources: Dataset, source code, presentation

Day 19: Face Emotion Recognition

• Project: Recognize human emotions from facial expressions
• Resources: Pre-trained models, dataset, source code, presentation