| # Skills & Expertise |
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|
| ## AI & Machine Learning |
| - Machine Learning (Supervised, Unsupervised, Reinforcement Learning) |
| - Deep Learning: ANN, CNN, RNN, LSTM |
| - Natural Language Processing (NLP) |
| - Computer Vision using OpenCV and YOLO |
| - Scikit-learn, TensorFlow, PyTorch |
| - Model training, evaluation, and deployment |
|
|
| ## Generative AI & LLMs |
| - Large Language Models (LLMs) — OpenAI, open-source LLMs |
| - Prompt Engineering |
| - LangChain and LangGraph for AI pipelines |
| - Agentic AI and Tool Calling |
| - Memory Management in AI systems |
| - RAG (Retrieval Augmented Generation) architectures |
| - OpenAI API and OpenRouter API integration |
| - LLM API routing across multiple model providers |
|
|
| ## Development & Tools |
| - Python (Primary language — Expert level) |
| - Flask and FastAPI for AI app deployment |
| - Streamlit for data apps and dashboards |
| - SQL for database management |
| - Git and GitHub for version control |
| - Jupyter Notebook and Google Colab |
| - Docker (containerization) |
| - Postman (API testing) |
|
|
| ## Data & Cloud |
| - NumPy, Pandas for data manipulation |
| - Matplotlib, Seaborn for data visualization |
| - Google BigQuery for cloud data |
| - Azure Data Factory for data pipelines |
| - AWS Cloud (certified) |
| - Google Cloud Platform (GCP) |
|
|
| ## Web & Other Technologies |
| - HTML5, CSS3, Bootstrap, Tailwind CSS |
| - Django, React Native (basic) |
| - MongoDB, MySQL, PostgreSQL, SQLite |
| - Figma (UI/UX design basics) |
| - Selenium, Hadoop, Kubernetes (exposure) |
|
|
| ## Soft Skills |
| - Problem solving and analytical thinking |
| - Quick learner and self-motivated |
| - Team collaboration |
| - Technical communication |
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