Core focus areas driving our certifications, Jupyter notebook labs, and academic research partnerships.
Deep dive into multi-head self-attention networks, tokenization, fine-tuning methodologies (LoRA/QLoRA), RAG pipelines, and deploying localized open-weights LLMs for scientific literature mining.
Optimization of PyTorch CUDA kernels, distributed GPU training protocols (DDP/FSDP), model quantization techniques (4-bit/8-bit), and memory-efficient training for complex neural datasets.
Machine learning models engineered specifically for whole-slide histopathology, single-cell spatial transcriptomics, molecular folding predictions (ESMFold), and AI drug screening pipelines.
Current hands-on certification workshops and live cohorts in Artificial Intelligence.
Distinguished academic leaders and industrial directors overseeing AI certification tracks.

Ai/Ml
Jawaharlal Nehru Technological University Hyderabad(JNTUH)
๐ฌ Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Natural Language Processing (NLP), and Applied Machine Learning
Expert AI Consultant
Visiting faculty members for various government and private organizations
๐ฌ Artificial Intelligence, Applied Machine Learning, & Deep-Tech Web Modeling
Assistant Professor
PhD (IIT Delhi)
๐ฌ Deep learning, Neural Networks, Reinforcement Learning , Generative AI, Natural Language Processing