Anjali Urunkar

About Anjali Urunkar

Anjali Urunkar Data Science Student Enthusiastic and driven data science student with a passion for leveraging data to solve real-world problems. Proficient in statistical analysis, and programming languages such as C, Python and R, HTML. Experienced in data collection, cleaning, and visualization, with a strong understanding of data-driven decision-making processes. Skilled in collaborative problem-solving and project management. Currently seeking opportunities to apply and to develop skills in a dynamic and innovative environment. Open to internships and full-time positions in the field of data science.

Experience

1. Data Science Intern

   Oasis Infobyte

   Present

   Tasks Performed: 1. Iris Flower Classification: Utilized machine learning classification models to accurately categorize iris flowers into distinct species (Setosa, Versicolor, Virginica) using the well-known Iris dataset. Unemployment Analysis with Python: Conducted in-depth analysis on national unemployment data, leveraging Python’s Pandas and NumPy libraries to clean and preprocess raw data. Applied statistical techniques to identify key trends and forecast potential job market outcomes. Sales Prediction using Python: Built predictive models to forecast sales data based on historical trends. Applied linear regression and decision tree regression models to predict future sales figures and provided actionable insights for business strategy. Role Overview: 1. Cleaned and Pre-processed raw Datasets using Python libraries such as Pandas and NumPy to ensure Data Quality and Reliability for Analysis. Conducted exploratory data analysis (EDA) on large datasets to uncover trends and insights, enabling informed decision-making. Developed Machine Learning Models using Scikit-Learn, focusing on Linear Regression and Logistic Regression to predict outcomes based on historical data. Built interactive Data Visualizations using Matplotlib and Seaborn to effectively communicate insights from the data. Skills Developed: 1. Programming: Enhanced Python coding proficiency, focusing on data manipulation and analysis. Data Cleaning and Preprocessing: Mastered techniques for handling missing values, encoding categorical data, and normalizing features. Data Visualization: Gained expertise in creating informative plots, histograms, and charts to visualize data trends and model performance. Machine Learning: Applied foundational machine learning algorithms and built models to solve problems.

Education

• Vivekanand College, Kolhapur

  HSC

  2022

• New Model English School Kolhapur

  SSC

  2020

• D. Y. Patil College of Engineering & Technology, KASABA BAWADA (DYPCET)

  Bachelor of Technology - BTech

  2022 — 2026