Secured 3rd Rank in University 24hr Hackathon TechWizard (2024) on Proctoring System project

Completed NVIDIA DLI's course on Building RAG Agents with LLMs. gained hands-on experience with LangChain, Gradio, and FAISS for document retrieval and dialog management.

Achieved Elite Badge in NPTEL Course Large Language Models (LLMs) Conducted in collaboration with IIT Delhi & IIT Bombay

Achieved Various GitHub batches through professional open-source collaborative developments.

Hi There,
I'm Nishant Singh

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About Me

Nishant Singh

Aspiring Data Scientist | DL Enthusiast

Passionate about building intelligent, production-ready AI systems with a strong focus on Deep Learning. Experienced across Computer Vision, Transformers, GANs, VAEs, and Retrieval-Augmented Generation (RAG). Skilled in designing models from scratch and fine-tuning architectures such as BERT, T5, YOLO, VGG, ResNet, R-CNN, and U-Net. Proficient in core machine learning methodologies and modern NLP frameworks including LangChain, Transformers, and LangGraph. Experienced in deploying scalable AI applications using Flask, Gradio, and Streamlit. My end-to-end projects on GitHub and Kaggle demonstrate practical, real-world AI solutions.

: 20 years

: At University

: nishantsingh.talk@zohomail.in

: Haridwar (UTTARAKHAND)

Resume

Certificate

Skills & Familiarity

Secured 3rd Rank in University 24hr Hackathon TechWizard on Proctoring System project

Streamlit

Transformer

OpenCV

numPy

Pandas

LangGraph

Keras

Advancedpy

LoRA

NLP

React

Django

Flask

HuggingFace

Seaborn

ScikitLearn

C/C++

work Experience

Banao Technologies AI Engineer Part-time

Aug - 2025 to PRESENT

Designing end-to-end AI systems with LangGraph/LangChain, API integrations, structured workflows, and database orchestration.
Applying advanced LLM techniques, including domain-specific fine-tuning, agentic AI research, prompt engineering, and retrieval optimization.

Haridwar University Data Science Intern

Jun - 2025 to Jul - 2025

Applied ML algorithms (Linear Regression, K-Means, ANN, CNN) on real-world datasets using Numpy, Pandas, and Matplotlib.
Used Scikit-learn and TensorFlow for end-to-end workflows and evaluated models with F1, MAE, MSE, and accuracy.

Onlei Technologies Data Science Intern

Jan - 2025 to Feb - 2025

Applied data preprocessing techniques including data cleaning, merging, and handling missing/null values to improve model accuracy, while strengthening foundational knowledge of data analysis pipelines and practical model training workflows.