Badges 1

• Getting Started16 Oct 2026

Recent tests

• TensorFlow & Keras

  Intermediate1 attempt
  0% best7 days ago

About

I am Udhaya Kumar S, a B.Sc. Computer Science graduate from Sri Sankara Arts and Science College, who completed my studies in 2026. During my academic journey, I worked on projects such as Movie Review Sentiment Analysis using LSTM and Kidney Disease Prediction using ANN, gaining hands-on experience with Python, TensorFlow, Keras, Pandas, NumPy, and Streamlit. I also completed an AI/ML internship at Edutantr, where I developed skills in data preprocessing, model building, and deployment. My strongest skills include Python, deep learning frameworks, and data analysis tools. I am now seeking my first full-time role as an ML Engineer, where I can contribute to data analysis, model development, and experimentation while continuing to grow in the field of AI/ML.

Experience

1. AI/ML Intern

   Edutantr

   Jun 2026 – Aug 2026 · Remote

   Completed a mentor-guided online AI/ML internship at Edutantr, gaining practical exposure to the end-to-end machine learning workflow, from data preparation to model building, training, and evaluation. Learned core machine learning and neural network concepts under mentor guidance and applied them through hands-on practice in Python. Practiced data cleaning and preprocessing to prepare raw datasets for model training, focusing on data quality and consistency. Strengthened problem-solving, self-learning, and time-management skills by completing all tasks independently in a fully online, remote environment.

Education

1. Sri Sankara Arts and Science College

   B.Sc. Computer Science

   2026 · Grade: 8.08 / 10

2. Cholan Matric Hr Sec School, Kanchipuram

   Higher Secondary Certificate (HSC)

   2021 – 2022 · Grade: 74%

Projects

• Movie Review Sentiment Analysis using LSTM (Deep Learning)

  • Python
  • TensorFlow
  • Keras
  • LSTM
  • Pandas
  • NumPy
  • Streamlit
  • Jupyter Notebook

  Prepared a clean, model-ready dataset from 50,000 IMDB movie reviews using tokenization, sequence padding, and embedding-based preprocessing. Built an LSTM-based sentiment classifier in TensorFlow/Keras achieving 85% test accuracy, tuning hyperparameters and architecture across multiple training experiments. Deployed the model as an interactive Streamlit web app with real-time predictions and documented the full workflow in a 12-slide technical presentation.

• Kidney Disease Prediction using ANN (Deep Learning)

  • Python
  • TensorFlow
  • Keras
  • Pandas
  • NumPy

  Prepared a model-ready dataset from a 400-record kidney disease CSV file for neural network training. Cleaned the data by removing stray tab characters and resolving data type mismatches. Built an Artificial Neural Network (ANN) to predict kidney disease as the minor project of the Edutantr AI/ML internship.

Certifications

• Python 3.4.3 Training

  Spoken Tutorial, IIT Bombay (EduPyramids) · 2026

Achievements

• Movie Review Sentiment Analysis using LSTM (Deep Learning)

  2026

  Prepared a clean, model-ready dataset from 50,000 IMDB movie reviews using tokenization, sequence padding, and embedding-based preprocessing.

• Kidney Disease Prediction using ANN (Deep Learning)

  2026

  Prepared a model-ready dataset from a 400-record kidney disease CSV file for neural network training.

• AI/ML Intern

  2026

  Completed a mentor-guided online AI/ML internship at Edutantr, gaining practical exposure to the end-to-end machine learning workflow, from data preparation to model building, training, and evaluation.

• Python 3.4.3 Training

  2026

  Python 3.4.3 Training with a score of 100% from Spoken Tutorial, IIT Bombay (EduPyramids).