Advance Artificial Intelligence
This comprehensive course delves into the core and advanced concepts of artificial intelligence, covering fundamental principles, neural networks, and specialized AI modules. Students will explore visual intelligence (CNNs, object detection), language intelligence (RNNs, Transformers, large language models), generative models (VAEs, GANs, Stable Diffusion), temporal intelligence (time series analysis, spatiotemporal networks), graph intelligence (graph neural networks), multimodal intelligence (data fusion, dual/multimodal models), and reinforcement learning (autonomous agents, RL algorithms). Through hands-on experiments, learners will gain practical insights into designing and implementing cutting-edge AI systems for diverse applications.
Github Repositories
| Project Name | GitHub Repo URL | Category |
|---|---|---|
| Convolutional Neural Network with Pytorch | https://github.com/kcsanjeeb/AI_Codes/blob/main/Neural-Network/cnn.ipynb | Convolutional Neural Network |
| Iris Flower Classification Neural Network with PyTorch | https://github.com/kcsanjeeb/AI_Codes/blob/main/Neural-Network/iris.ipynb | Neural Network |