Neural Networks, Image Processing, Natural Language Processing, Deep learning techniques, On-premises infrastructure, Cloud AI services, Generative AI models

probability , Deep Learning, Testing Frameworks, AI evaluation methodologies, ML algorithms, fine-tuning model adaptation, deploying ML models as APIs, production-quality AI code, vector databases, LLM customization, prompt engineering, AI model monitoring, RAG techniques, AI pipelines, drift detection, LLM architectures, linear algebra, Governance, cloud-native AI architectures

Python, Sql, tree-based models, R, observability monitoring tools, Generative AI tooling, time-series forecasting, classical ML modeling

Tensorflow, Pytorch, MLops, Python, Cuda, SageMaker, NVIDIA

Github, BigQuery, Google Cloud Platform, PostgreSQL, Jira, Django, Cloud Storage, FastAPI, DataFlow, Python, LangChain, vector databases, Cloud Run, Vertex AI, AI agents, GenAI orchestration frameworks, RAG pipelines, Google ADK

Java, Cassandra, PostgreSQL, Dynamodb, Kafka, Redis, Sql, Tensorflow, Nosql, Pytorch, Docker, MySQL, Spark, Kubernetes, Python, Go

Tensorflow, Pytorch, Docker, Databricks, DataFlow, Azure Machine Learning, Kubernetes, Python, LangChain, AWS Bedrock, Hugging Face, Azure OpenAI, GCP Vertex AI, BigQuery ML, AWS SageMaker

Nosql, Tensorflow, Shell, Pytorch, Cicd, Python, AWS, Natural Language Processing, PowerShell, Sql, Django, Git, REST, Gcp, FastAPI, Keras, Azure, Azure Devops, Github Actions, Chat GPT, LangGraph, LangChain, AI Observability, AI Guardrails, Open AI, Vector Database, RAG, DsPy, Responsible AI, LlamaIndex, Prompt Engineering