data engineering , regression models , Machine Learning, MLops, Python, Sql, Deep Learning, anomaly detection, Classification Models, Boosted Models, Simulation Problems

Ml, Deep Learning, Python, Nlp, MLops, ranking, Model packaging, Forecasting, Classification, anomaly detection, LLM-based applications

BigQuery, Cloud Storage, tool integration, embeddings, Prompt engineering, Agent loops, Agentic AI Basics, memory fundamentals, Coding Proficiency in Python, Pub Sub, GenAI Basics, Vertex AI, simple RAG concepts, GCP Services, familiarity with APIs and SDKs

bedrock , Tensorflow, Lambda, Pytorch, MLops, Docker, ECS, XGBoost, Kubernetes, Python, AWS, Airflow, scikit-learn, Hugging Face Transformers, LightGBM, MLflow, EKS, SageMaker, Kubeflow

MLops, Python, AWS, NLP systems, multi-agent systems, cloud-based AI deployments, Llm, RAG, AI frameworks

Tensorflow, Time Series Analysis, Pytorch, image processing techniques, Forecasting, reinforcement learning, computer vision algorithms

Python, System Prompt Engineering, Tool Chaining

Pandas, Sql, Tensorflow, Numpy, MLops, Pytorch, Python, Docker, Apis, Nlp, Git, scikit-learn, ETL processes

Gitlab, Sql, Tensorflow, Pandas, Pytorch, Gcp, Git, XGBoost, Github, Numpy, AWS, Kubernetes, Python, Azure, Docker, Jenkins, Airflow, GitLab CI, scikit-learn, CoreML, Neptune.ai, TensorRT, GitHub Actions, MLflow, LightGBM, TensorBoard, TFLite

Tensorflow, Distributed Computing, Pytorch, Big Data Technologies, Python, scikit-learn, cloud platforms, machine learning techniques