Skip to content
View pratikschitnis's full-sized avatar
7 followers · 7 following

Block or report pratikschitnis

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don't include any personal information such as legal names or email addresses. Markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
pratikschitnis/README.md

Hi there, I'm Pratik Chitnis 👋

📊 Turning Data into Insights | 🤖 Exploring Machine Learning | 🚀 Growing with Purpose

👨‍💻 About Me

🎓 Completed CDAC in Advanced Computing | Currently pursuing Data Science

💡 Passionate about solving real-world problems using data-driven approaches

📊 Skilled in Python, SQL, Pandas, NumPy, Matplotlib, Seaborn, Power BI

📈 Experienced in EDA, Hypothesis Testing, Regression, and Business Analytics

🚀 Exploring ML, Time Series, and Model Deployment

🌟 What I’m Working On

📌 Building hands-on projects in data cleaning, analysis & visualization

📚 Exploring machine learning techniques and real-time data applications

📊 Designing interactive dashboards in Power BI for business insights

✨ Lifelong learner with a problem-solving mindset

💼 Tools I Use

📈 GitHub Stats

GitHub stats Top Languages

Contribution Graph

🔗 Let's Connect

LinkedIn

"Data is the new oil, and I love refining it into insights!"

Pinned Loading

  1. Diwali_sales_analysis Diwali_sales_analysis Public

    Analyzed company’s Diwali sales data to uncover customer purchasing patterns and product performance. The project involved data cleaning, EDA, and visualization using Python libraries (Pandas, NumP…

    Jupyter Notebook

  2. FMCG-Sales-Dashboard FMCG-Sales-Dashboard Public

    Built an interactive dashboard in Power BI to analyze FMCG sales trends. Visualized KPIs like revenue, units sold, and average price with dynamic slicers for region, brand, category, and year. #Pow…

  3. titanic-survival-eda titanic-survival-eda Public

    Explored the Titanic dataset using Python and Pandas to uncover survival patterns. Performed data cleaning, feature engineering, and EDA with visualizations. Identified key factors like gender, cla…

    Jupyter Notebook