Curriculum
- 15 Sections
- 150 Lessons
- 10 Weeks
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- Introduction to Artificial Intelligence10
- 1.1Introduction to Artificial Intelligence
- 1.2History and Evolution of AI
- 1.3Types of Artificial Intelligence
- 1.4Narrow AI vs General AI
- 1.5Artificial Intelligence vs Machine Learning
- 1.6Artificial Intelligence vs Data Science
- 1.7Real-World Applications of AI
- 1.8AI Industry and Career Opportunities
- 1.9Understanding Intelligent Systems
- 1.10Setting Up the AI Learning Environment
- Python for Artificial Intelligence10
- Mathematics and Statistics for AI10
- Data Preparation for AI10
- Machine Learning Fundamentals10
- 5.1Introduction to Machine Learning
- 5.2Types of Machine Learning
- 5.3Supervised Learning
- 5.4Unsupervised Learning
- 5.5Reinforcement Learning Overview
- 5.6Machine Learning Workflow
- 5.7Training and Testing Data
- 5.8Overfitting and Underfitting
- 5.9Introduction to Scikit-learn
- 5.10Machine Learning Fundamentals Project
- Supervised Learning Algorithms10
- Unsupervised Learning Algorithms10
- Deep Learning Fundamentals10
- Advanced Deep Learning10
- Natural Language Processing10
- Computer Vision10
- Generative AI Fundamentals10
- 12.1Introduction to Generative AI
- 12.2Generative AI vs Traditional AI
- 12.3Understanding Large Language Models
- 12.4Introduction to Transformers
- 12.5Prompt Engineering Fundamentals
- 12.6AI Content Generation
- 12.7AI Image Generation Concepts
- 12.8AI-Powered Applications
- 12.9Responsible Generative AI
- 12.10Generative AI Mini Project
- AI Model Deployment10
- AI Ethics and Responsible AI10
- AI Live Projects and Capstone10
- 15.1AI-Based Prediction Project
- 15.2Customer Churn Prediction
- 15.3Image Classification Project
- 15.4Sentiment Analysis Project
- 15.5NLP Chatbot Project
- 15.6Computer Vision Application
- 15.7Generative AI Application
- 15.8AI Model Deployment Project
- 15.9End-to-End Artificial Intelligence Project
- 15.10Final Artificial Intelligence Capstone Project
End-to-End Artificial Intelligence Project
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