All Categories

Healthcare, finance, marketing, education, etc.

Bias, fairness, explainability, regulations.

Basics of AI, intro to concepts like neural networks, supervised learning, etc.

MLOps, scaling models, monitoring, CI/CD.

Python, TensorFlow, PyTorch, JAX.

Image classification, object detection, OCR.

Data cleaning, EDA, statistics, feature engineering.

Data collection, preparation, and analysis for AI applications

Neural networks, CNNs, RNNs, transformers.

Resources on ethical considerations, fairness, and responsible AI development

Supervised/unsupervised learning, algorithms, model training, etc.

Text, speech, chatbots, LLMs.

Trust, safety, fairness, transparency.