data engineering , Artificial Intelligence - BASIC, Generative AI - Basic, Machine Learning, Databricks, AI-Generative AI, Technology, AI-Data science

Sql, Pandas, Vector databases design scaling optimization, NLP systems and production AI pipelines, Prompt engineering advanced, Polars, GPU basics, Model fine-tuning concepts, LangChain, RAG architectures, Agentic AI design, LangGraph, Python advanced

Git, Angular, Python, Kubernetes, Github, Docker, SQL and NoSQL databases

Computer Vision, C, Tensorflow, AI ML, Opencv, Linux, Pytorch, Cuda, Kubernetes, Python, Docker, Git, cloud platforms, ONNX, Real-time video processing, RTSP video streaming, TensorRT

Tensorflow, Pytorch, Python, Docker, Pandas, Git, Numpy, scikit-learn, Performance evaluation metrics, Data preprocessing and feature engineering, Model selection training and hyperparameter tuning, Clear technical documentation and reporting

Computer Vision, Nlp, deep learning concepts, machine learning concepts

amazon web services aws , Tensorflow, Pytorch, Data Structures, Python, Windows Azure, Neural Networks, Google Cloud Platform GCP, Artificial Intelligence AI, Transfer Learning, Feature Engineering, Data Preprocessing, Machine Learning ML, Deep Learning Architectures, Scikit-Learn

Github, Tableau, Tensorflow, Numpy, Seaborn, Pytorch, Swagger, XGBoost, Gitlab, Python, Api Gateway, Oauth, Hadoop, Power Bi, Jwt, Devops, Git, Pandas, Matplotlib, Spark, Keras, Restful Apis, Postman, Kubernetes, scikit-learn, MLOps practices, Large Language Models, Plotly, LightGBM, ML libraries, Jupyter Notebooks, OpenAPI

Python, AI ML, Debugging and troubleshooting techniques