probability , Deep Learning Frameworks (e.g., TensorFlow), Machine Learning, C++, Neural Networks, Pytorch, Algorithms, Pattern Recognition, Python, Statistics, Model Optimization, Data Processing, Experimental Design

Video Processing, Tensorflow, Pytorch, Opencv, Python, ML deep learning fundamentals, IMU wearable sensor-fusion, Media Pipe, Signal Processing, scikit-learn, human activity recognition, time-series modelling, pose estimation

data engineering , Technical Leadership, python, Pytorch, Deep Learning, Machine Learning, Numpy, MLops, Azure, retrieval-augmented generation, vector search, langchain, mentorship, model deployment, embeddings, langgraph, llmops, agentic ai, production integration, model serving, prompt engineering, pipeline architecture

Keras, Sql, Decision Trees, Tensorflow, Pytorch, Python, Arima, Hypothesis Testing, Statistical Analysis, Z-Test, CNTK, Great Expectations, T-Test, Regression, probabilistic graph models, MXNet, support vector machines, exponential smoothing, ARIMAX, Sci-Kit Learn, KubeFlow, BentoML, Evidently AI

Python Programming, Databricks, Agent Frameworks Libraries, Prompt engineering

Retrieval-Augmented Generation (RAG), MLops, Docker, Python, AWS, LangChain, GenAI, Generative AI, AWS Bedrock, Prompt engineering, Model monitoring, SageMaker, Vector Databases, OpenAI APIs, Containerized deployments, LLM evaluation

Java, BigQuery, Apis, Cloud Storage, Python, Google Enterprise Agent Platform, GenAI, Prompt engineering, Pub Sub, Embeddings, RAG pipelines, SDKs, ADK frameworks, GCP services