Learn the Foundations of Machine Learning, Explore AI Concepts, and Build Real-World Neural Network Models Using Python.
Sub Category
- Data Science
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Objectives
- What is Machine Learning
- AI & Neural Networks
- Setting Up Your ML Environment
- Python Basics & Essential Libraries
- Data Handling & Preprocessing with Pandas
- Data Visualization Techniques
- Handling Missing Data & Data Cleaning
- Feature Scaling & Normalization
- Encoding Categorical Data
- Understanding Regression in ML
- Simple & Multiple Linear Regression
- Logistic Regression & Decision Trees
- Model Evaluation & Cross-Validation
- Introduction to Deep Learning & Neural Networks
- Building a CNN for Image Classification
- Object Detection & Image Segmentation
- Understanding Sequential Data & Time Series
- Natural Language Processing
- AI in Creative Fields (Music, Art, Video)
- Future of AI & ML (Quantum Computing, AGI)
- AI Career Paths & Industry Opportunities
Pre Requisites
- Basic Programming experience needed
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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