AI-For-Beginners: 12 Weeks, 24 Lectures: Code Implementation from BERT to LLMs

This is a 12-week, 24-lecture course covering AI fundamentals to advanced topics. It teaches neural networks and deep learning principles through hands-on code implementation using TensorFlow and PyTorch. Each lecture consists of pre-reading materials, executable Jupyter Notebooks, and labs for certain topics.

Focusing on computer vision and natural language processing (NLP), it covers modern architectures such as CNN, RNN, Transformer, BERT, and LLM. It broadly covers lesser-known techniques like genetic algorithms, reinforcement learning, and multi-agent systems, as well as AI ethics. In contrast, traditional machine learning, specific cloud frameworks, and chatbot development are separated into distinct curricula.

For complete beginners, it provides simple examples ranging from pattern recognition to image classification and text sentiment analysis. It is automatically translated into over 50 languages, making it accessible to global learners. It is suitable for developers and educators new to AI who want to systematically build a strong foundation.