I am Monika Mohankumar, a B.Tech graduate in Artificial Intelligence & Data Science from Kangeyam Institute of Technology, Tirupur, Tamil Nadu, with a CGPA of 8.83. During my studies, I completed several projects, including an AI Support Ticket Assistant using LLMs and an AI & IoT Industrial Tank Safety System, which was published in ICECT 2026. I also completed a one-month internship as a KNIME Data Analytics Intern, where I built AI-driven dashboards and data workflows. My strongest skills include Python, SQL, prompt engineering, LLM application development, and TensorFlow. I am seeking my first full-time role as a Data Analyst.
Experience
KNIME Data Analytics Intern
Global Knowledge Technologies
2024 – 2024 · Remote
Built 3+ AI-driven dashboards and data workflows on real client datasets; delivered analytical reports for 2 client presentations, reducing manual reporting effort by ~40%.
Education
Kangeyam Institute of Technology, Tirupur, Tamil Nadu
B. Tech, Artificial Intelligence & Data Science
2022 – 2026 · Grade: 8.83/10
Projects
AI Support Ticket Assistant (LLM Application)
Python
Llama 3.2
Ollama
Pandas
FastAPI
Streamlit
Built an LLM-powered assistant for natural-language questions over 500 support tickets: Llama 3.2 3B (Ollama) classifies intent, and Pandas computes the answers to avoid hallucinated figures. Exposed 7 FastAPI REST endpoints with a Streamlit UI and added statistical anomaly detection.
AI & IoT Industrial Tank Safety System (Research)
Python
Sensor Fusion
LLM
Research
Designed a real-time sensor-fusion pipeline for confined industrial spaces; automated alerts reduced simulated response time by 40%. Co-authored and issued paper at ICECT 2026 (ISBN 978-93-5737-886-4, pp. 392–398).
Spotify Listening Trends Dashboard (Analytics)
Python
MySQL
Excel
Built an end-to-end analytics solution (Python, MySQL, Excel) on 10,000+ records; resolved 1,200+ duplicates and cut ad-hoc reporting time by ~60% with interactive dashboards.
Handwritten Digit Recognizer (Deep Learning)
Python
TensorFlow
CNN
Trained a CNN on MNIST to 98.6% accuracy by tuning learning rate, dropout and batch size with the Adam optimizer and LR scheduling.
Health Diagnosis Pipeline (Analytics)
KNIME
HTML
CSS
Built a KNIME workflow on 500+ clinical records surfacing 3 diagnostic patterns; created an HTML/CSS interface for non-technical clinicians.
Certifications
AWS Cloud Practitioner Essentials
AWS Training & Certification
Cloud Computing
NPTEL
Foundations of IoT Edge ML
NPTEL
Introduction to Data Science
Infosys Springboard
Modern Web Development by Example
Infosys Springboard
Data Science (British Airways)
Forage
Data Analytics (Deloitte)
Forage
Achievements
Intelligent AI–IoT Framework for Real-Time Safety Monitoring and Automated Rescue in Confined Industrial Spaces
2026
Co-authored and issued paper at ICECT 2026 (ISBN 978-93-5737-886-4, pp. 392–398).
Monika Mohankumar
B.Tech Artificial Intelligence & Data Science graduate from Kangeyam Institute of Technology, Tirupur, Tamil Nadu
I am Monika Mohankumar, a B.Tech graduate in Artificial Intelligence & Data Science from Kangeyam Institute of Technology, Tirupur, Tamil Nadu, with a CGPA of 8.83. During my studies, I completed several projects, including an AI Support Ticket Assistant using LLMs and an AI & IoT Industrial Tank Safety System, which was published in ICECT 2026. I also completed a one-month internship as a KNIME Data Analytics Intern, where I built AI-driven dashboards and data workflows. My strongest skills include Python, SQL, prompt engineering, LLM application development, and TensorFlow. I am seeking my first full-time role as a Data Analyst.
Experience
KNIME Data Analytics Intern
2024 – 2024
Global Knowledge Technologies, Remote
Built 3+ AI-driven dashboards and data workflows on real client datasets; delivered analytical reports for 2 client presentations, reducing manual reporting effort by ~40%.
Education
Kangeyam Institute of Technology, Tirupur, Tamil Nadu
2022 – 2026
B. Tech, Artificial Intelligence & Data Science · Grade: 8.83/10
Built an LLM-powered assistant for natural-language questions over 500 support tickets: Llama 3.2 3B (Ollama) classifies intent, and Pandas computes the answers to avoid hallucinated figures. Exposed 7 FastAPI REST endpoints with a Streamlit UI and added statistical anomaly detection.
AI & IoT Industrial Tank Safety System (Research)
Python, Sensor Fusion, LLM, Research
Designed a real-time sensor-fusion pipeline for confined industrial spaces; automated alerts reduced simulated response time by 40%. Co-authored and issued paper at ICECT 2026 (ISBN 978-93-5737-886-4, pp. 392–398).
Spotify Listening Trends Dashboard (Analytics)
Python, MySQL, Excel
Built an end-to-end analytics solution (Python, MySQL, Excel) on 10,000+ records; resolved 1,200+ duplicates and cut ad-hoc reporting time by ~60% with interactive dashboards.
Handwritten Digit Recognizer (Deep Learning)
Python, TensorFlow, CNN
Trained a CNN on MNIST to 98.6% accuracy by tuning learning rate, dropout and batch size with the Adam optimizer and LR scheduling.
Health Diagnosis Pipeline (Analytics)
KNIME, HTML, CSS
Built a KNIME workflow on 500+ clinical records surfacing 3 diagnostic patterns; created an HTML/CSS interface for non-technical clinicians.
Skills
Python
SQL (MySQL)
C
HTML
CSS
LLM application development
Prompt Engineering
Intent Classification
Ollama (Llama 3.2)
Streamlit
RAG
TensorFlow
FastAPI
Docker
REST APIs
Git
Pandas
NumPy
Matplotlib
Seaborn
Power BI
Tableau
MS Excel
KNIME
XGBoost
Certifications
AWS Cloud Practitioner Essentials
AWS Training & Certification
Cloud Computing
NPTEL
Foundations of IoT Edge ML
NPTEL
Introduction to Data Science
Infosys Springboard
Modern Web Development by Example
Infosys Springboard
Data Science (British Airways)
Forage
Data Analytics (Deloitte)
Forage
Achievements
Intelligent AI–IoT Framework for Real-Time Safety Monitoring and Automated Rescue in Confined Industrial Spaces
2026
Co-authored and issued paper at ICECT 2026 (ISBN 978-93-5737-886-4, pp. 392–398).
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