Artificial Intelligence

Description

Description:
This internship provides a hands-on introduction to Artificial Intelligence. Interns will learn to build intelligent systems that can analyze data, make predictions, and automate decisions. Through real-world projects, participants gain practical experience in machine learning, deep learning, and AI model deployment.

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🧠 Practical Curriculum Outline

Week 1: Introduction to AI & Python for AI

• What is AI, ML, and Deep Learning

• Setting up Python environment (Anaconda, Jupyter Notebook)

• Python libraries for AI: NumPy, Pandas, Matplotlib

• Mini Task: Data visualization using real-world datasets

Week 2: Machine Learning Fundamentals

• Supervised vs. Unsupervised Learning

• Regression and Classification algorithms

• Model training, testing, and evaluation

• Mini Project: Predict student performance using ML

Week 3: Deep Learning with Neural Networks

• Understanding Artificial Neurons & Activation Functions

• Building Neural Networks using TensorFlow/Keras

• Convolutional Neural Networks (CNNs) for image data

• Mini Project: Handwritten digit recognition (MNIST dataset)

Week 4: Natural Language Processing (NLP)

• Text cleaning, tokenization, and feature extraction

• Sentiment analysis with real Twitter data

• Mini Project: AI Chatbot using NLP

Week 5: AI in Real-world Applications

• AI for healthcare, finance, and autonomous systems

• Model deployment using Flask/Streamlit

• Final Project: End-to-end AI solution (choose your domain)

Week 6: Evaluation & Certification

• Project presentation

• Evaluation by mentors

• Certification of Completion

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💡 Outcome:

By the end of this internship, interns will:
✅ Build and deploy AI models independently
✅ Gain real-world problem-solving experience
✅ Strengthen portfolio with practical AI projects