Deepali Dagar | Data Science Professional 

Data Science Master's student from the University of Chicago, with a strong foundation in Machine Learning and Applied Generative AI

Tech Stacks

• Languages & ML Frameworks: Python (NumPy, Pandas, Scikit-Learn, PyTorch, TensorFlow, Keras), SQL, PySpark, R
• GenAI & AI Tooling: LangChain, LangGraph, Agentic AI (A2A), Vector Databases (FAISS, Pinecone, ChromaDB), RAG Pipelines, Prompt Engineering, Whisper STT, TTS Models (Bark), Multi-Model Orchestration (MCP)
• Data Visualization: Tableau, Power BI, Matplotlib, Seaborn, Excel
• Big Data & Cloud: Google Cloud Platform (GCP), AWS, Spark, Hadoop, Hive, Docker, MapReduce
• Key Skills: Supervised & Unsupervised ML, Predictive Modeling, Deep Learning, Feature Engineering, MLOps, LLM Applications & Agents

Key Coursework

• Machine Learning
• Big Data and Cloud Computing
• Generative AI
• Data Structures and Algorithms
• Python for Data Science
• Statistics
• Probability
• Algorithmic Marketing
• Discrete Mathematics
• Linear Algebra
• Calculus
• Differential Equations
• Algebra

Currently working on:

• GenAI Audio-to-Audio E-commerce Chatbot: Voice-based product assistant using Whisper STT, ChromaDB vector search, and OpenAI TTS for context-aware recommendations.

• Multi-Agent Customer Service System leveraging A2A messaging and MCP for dynamic tool orchestration

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