Natural language processing techniques, AI pipelines for data processing and model training

API development and integration, Python, Monitoring observability or MLOps concepts, Agentic frameworks or orchestration patterns, Generative AI and LLMs, Tool calling and action execution, CI CD and modern DevOps practices

Distributed Computing, Hadoop, Tensorflow, Pytorch, Spark, Python, LLMs, model versioning, prompt engineering, big data tools, MLOps tools, ML frameworks

Python, machine learning fundamentals, model training, inference pipelines, evaluation pipelines, production-quality code

Natural Language Processing, AI ML, Tensorflow, Pytorch, Python, Generative AI, Langchain, Transformers, LLMs, scikit-learn, Hugging Face, Pinecone, anomaly detection, prompt engineering, spaCy, Word2Vec, FAISS, TF-IDF, BERT, ChromaDB, Langraph

Scrum, Sql, Tensorflow, Nlp, Pandas, Pytorch, Docker, Agile, Azure, Python, AWS, embeddings, scikit-learn, vector databases, CI CD, Transformers, RAG pipelines

Tensorflow, Pytorch, Python, LangChain, vector search, fine-tuning, LLMs, Pinecone, Embeddings, RAG, ML frameworks, prompt design, Weaviate, LlamaIndex