About Lesson
Explore supervised learning methods such as linear regression, decision trees, and classification techniques with practical examples.
Module 1: Introduction to AI & Machine Learning
Understand the fundamentals of AI, ML concepts, applications, and industry use cases.
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Module 2: Python for AI & ML
Learn Python basics, libraries, and tools used for AI and machine learning development.
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Module 3: Data Analysis & Preprocessing
Work with data, clean datasets, and prepare data for machine learning models.
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Module 4: Machine Learning Algorithms
Understand supervised and unsupervised learning algorithms and model evaluation.
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Module 5: Model Training & Evaluation
Learn how to train models, tune performance, and evaluate results effectively.
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Module 6: Introduction to Deep Learning
Explore neural networks, deep learning concepts, and real-world applications.
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Module 7: AI Tools & Applications
Work with AI tools, frameworks, and practical implementation techniques.
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Module 8: Final Project & Deployment
Build and deploy an AI or ML project to demonstrate practical skills.
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