Algorithms, Cloud Services, Version Control, data structures, Rest Apis, Python, LLMs, prompt-engineering techniques, NLP libraries

data engineering , Quality, Pytorch, Debugging, Python, Linux Environment, Transformer deep learning fundamentals, Memory, latency, Mixing, Benchmarking, Hugging Face, Distillation, filtering, quantization, LLM training paradigms, DeepSpeed, Cleaning, SFT, distributed training, Accelerate, multi-GPU parallelism, pretraining, Analysis, model compression, end-to-end experiment running, LoRA, preference optimization, hyperparameter tuning

Pytorch, Tensorflow, Python, Image Processing, Machine Learning, AIGC, Large Vision-Language Generation Models