class AasimAnsari:
def __init__(self):
self.name = "Mohd Aasim Ansari"
self.role = "Aspiring Data Scientist & AI Engineer"
self.expertise = ["Data Science", "Machine Learning", "Deep Learning",
"NLP", "Computer Vision", "Gen AI", "RAG Pipelines",
"Agentic AI", "Multi-Agent Systems", "Full Stack Development"]
self.stack = {
"Data Science" : ["Pandas", "NumPy", "scikit-learn", "XGBoost",
"TensorFlow", "PyTorch", "Matplotlib", "Seaborn"],
"Gen AI" : ["LangChain", "LangGraph", "OpenAI API", "HuggingFace",
"RAG", "Groq", "Ollama", "LlamaIndex"],
"Agentic AI" : ["CrewAI", "AutoGen", "LangGraph", "Multi-Agent Systems"],
"Full Stack" : ["Python", "React", "FastAPI", "Node.js", "MongoDB",
"TailwindCSS", "Flask", "TypeScript"],
}
self.current_focus = "Full Stack Data Science with Gen AI and Agentic AI"
self.open_to = ["Full-Time Roles", "Internships", "Open Source Contributions", "Collaborations"]
def __repr__(self):
return "Always learning. Always building. Always delivering. 🚀"The full pipeline — from raw data to deployed agents · ⭐ marks what I have shipped in a project
Python ⭐ |
JavaScript ⭐ |
TypeScript ⭐ |
Bash |
MySQL |
PostgreSQL ⭐ |
MongoDB ⭐ |
Pandas ⭐ |
NumPy ⭐ |
SciPy |
Matplotlib ⭐ |
Seaborn ⭐ |
Plotly ⭐ |
Jupyter ⭐ |
scikit-learn ⭐ |
![]() XGBoost ⭐ |
LightGBM ⭐ |
CatBoost ⭐ |
TensorFlow |
PyTorch |
OpenCV ⭐ |
OpenAI ⭐ |
HuggingFace |
LangChain |
LlamaIndex |
Ollama |
Groq |
LangGraph |
CrewAI |
MCP |
React ⭐ |
Vite ⭐ |
Tailwind ⭐ |
Streamlit ⭐ |
Node.js ⭐ |
Express ⭐ |
FastAPI ⭐ |
Flask ⭐ |
Socket.IO ⭐ |
JWT ⭐ |
Docker ⭐ |
Git ⭐ |
GitHub ⭐ |
Linux ⭐ |
Actions ⭐ |
Render ⭐ |
VS Code |
Postman |
Anaconda |
Figma |







