Here’s a structured sequence to learn AI from scratch, along with the best online resources to guide you through each topic.
1. Introduction to AI
- Topic: Basics of AI, History, and AI Terminologies
- Resources:
2. Mathematics for AI
- Topic: Linear Algebra, Calculus, Probability, and Statistics
- Resources:
3. Programming for AI
- Topic: Python Programming, Libraries like NumPy, Pandas, and Matplotlib
- Resources:
4. Machine Learning Basics
- Topic: Supervised and Unsupervised Learning, Regression, Classification
- Resources:
5. Deep Learning
- Topic: Neural Networks, Convolutional Networks, Recurrent Networks
- Resources:
6. Natural Language Processing (NLP)
- Topic: Text Processing, Sentiment Analysis, Transformers, GPT Models
- Resources:
7. Generative AI
- Topic: GANs, VAEs, Transformers
- Resources:
8. Reinforcement Learning
- Topic: Markov Decision Processes, Q-Learning, Policy Gradients
- Resources:
9. AI Ethics
- Topic: Bias in AI, Ethical AI Practices, Regulations
- Resources:
10. AI Projects and Research
- Topic: Building AI Models, Research in AI
- Resources:
These resources should provide a comprehensive pathway to learning AI, from foundational concepts to advanced topics and applications.