data wrangling , Cloud Infrastructure, Containers, Python, vector search systems, LLMs, model training, RAG-based systems, CI CD, document knowledge bases, NLP tasks, traditional ML models, feature extraction, large language models, LlamaIndex

CDK, Typescript, FastAPI, Python, Terraform, Docker, Flask, OpenAI, LlamaIndex, Google, Azure OpenAI, LangChain, AWS Bedrock, Anthropic

Tensorflow, Nlp, Pytorch, Docker, Python, AWS, Gcp, Azure, Kubernetes, GloVe, Hugging Face, vector databases, MLflow, Pinecone, LLM architecture, MLOps practices, Word2Vec, RAG pipelines, ChromaDB, fine-tuning techniques, LangChain, APIs from major AI providers, embedding preparation, text processing, LLM training methodologies, Neural Network fundamentals, sentence transformers, cloud computing platforms

Distributed Systems, Python, multimodal systems, vector databases, Pinecone, custom retrieval layers, Swarm, Chroma, transformer architectures, RLHF, LangChain, CrewAI, AI safety, agent frameworks, AutoGen, LLM fine-tuning, LoRA, MLOps tooling, generative AI models, Milvus, OpenAI, Weaviate, QLoRA, LlamaIndex, red-teaming

Nlp, FastAPI, AWS, Deep Learning, Machine Learning, Huggingface, Generative AI

Databases, Flask, Api, FastAPI, Python, Sql, ML Fundamentals, FAISS, Gradio, Streamlit, ChromaDB

Numpy, Pandas, Python, Data Analysis, Statistical Modeling, Forecasting, decision-support systems, anomaly detection, time-series analysis, machine learning techniques