SANJAY S C

Looking for lucrative opportunities in the field of Data Science result-oriented and a motivated Data Science enthusiast looking to leverage my programming skills in Python, Statistics, MySQL, and Tableau. Possesses a comprehensive understanding of data analysis and machine learning concepts gained through my Masters Degree in DSML. Proven ability to spearhead projects in Python, Statistics, and Machine Learning, showcasing a strong problem-solving skills. Adept at leveraging statistical techniques to extract meaningful insights from data, with a solid foundation in database management using MySQL. Proficient in creating compelling visualizations in Tableau to communicate complex findings effectively. Eager to apply acquired skills and contribute to data-driven decision-making in a dynamic professional environment.

Modelling:   2D and 3 D Modelling using Solid Edge and CATIA V5.

Statistics:   Hypothesis Testing, Probability and Distribution, Bayes Theorem.

Machine Learning:   Supervised and Unsupervised, Regression, Classification, Clustering, Bagging,   Boosting and Optimization.

Deep Learning:   Neural Network, Tensor Flow, ANN, CNN, Image Processing using open CV,   Transfer Learning, Object Localization, Object Detection_YOLO, Semantic    Segmentation, Siamese Network.

Degree:   M Tech (Thermal Power Engineering)

Project Title:  Numerical Simulation of Turbulent Flow through a tube with Triple Helical Tape Inserts

Technology Used: CFD Fluent.

Description:   The project is carried out by using CFD Fluent software, where a model and meshing of   a typical circular tube with tape inserts have been carried out under various Reynolds   number and various parameters like heat flux and nusselt number is analyzed to   achieve convergence.

Degree:  M Tech (Data Science and Machine Learning) Pursuing

Mini Projects:

1. Dynamic Price Prediction of Airlines using Random Forest Regressor

2. Blue Bikes project using Tableau

3. Productivity Prediction of Garment Employees using Hypothesis Testing

4. Tesla Car & Lithium Battery Case Study using Tableau

Hackathons:

1. Employee Attrition using different algorithms to predict whether

2. Whether an employee will leave the company based on the various variables given in the  dataset.

3. Fake vs Real image detection using Deep Learning Techniques

4. Sunspot Count using ARIMA model of Time Series Forecasting

5. Sentiment Analysis using Natural Language Processing