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Chanikya333-1/README.md

Hi 👋, I'm Chanikya Kothi

Aspiring Data Engineer · Data Analytics Enthusiast · Cloud & ML Explorer

Boy Coding GIF

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📝 About Me

I’m Chanikya Kothi, an aspiring Data Engineer / Data Analyst, passionate about designing data pipelines, analytics dashboards, and cloud-native solutions.

  • 🎓 Master’s in Data Science, Wichita State University
  • 🎓 B.Tech in Electronics & Communication Engineering, SNIST
  • 🧰 Skilled in ETL pipelines, SQL, Python, Power BI, and cloud platforms
  • 🌟 Interests: Data engineering, analytics, machine learning, workflow automation

🎓 Education

  • Master’s in Data Science
    Wichita State University

  • Bachelor of Technology in Electronics & Communication Engineering
    SNIST

🎖️ Certifications

  • 🌩️ AWS Certified Cloud Practitioner

🧠 Skills

Programming & Query Languages:
Python SQL R Bash

Data Science & ML:
pandas NumPy scikit-learn XGBoost TensorFlow Keras

Data Visualization:
Power BI Tableau Matplotlib Seaborn Plotly

Data Engineering:
Apache Airflow dbt Apache Spark Apache Kafka ETL

Cloud Platforms:
AWS GCP

Databases:
PostgreSQL MySQL SQLite

DevOps & Tools:
Git GitHub Docker Jupyter VS Code

⚡ Hobbies

  • 🚘 Cars
  • 🛣️ Long drives
  • 👥 Spending time with friends
  • ✈️ Trips & exploring new places

🔗 Let’s Connect

⚡ Data pipelines, dashboards, and scalable solutions — one project at a time! ⚡

Pinned Loading

  1. customer-churn-prediction-using--ML customer-churn-prediction-using--ML Public

    Predicting customer churn using machine learning algorithms — includes data preprocessing, EDA, model training (Logistic Regression, Random Forest, XGBoost) and evaluation.

    Jupyter Notebook

  2. Handwritten_Digits_Recognition Handwritten_Digits_Recognition Public

    Handwritten digit recognition using Convolutional Neural Networks (CNN) on the MNIST dataset — deep learning for image classification.

    Jupyter Notebook

  3. HR_Analytics_dashboard HR_Analytics_dashboard Public

    Interactive Power BI dashboard for HR analytics — visualize employee attrition, performance, satisfaction, demographics, and training insights.

  4. Retail_Sales_Forecasting_Using-Time-Series-Models Retail_Sales_Forecasting_Using-Time-Series-Models Public

    Retail sales forecasting project using ARIMA, Prophet, XGBoost, and LSTM — compares time series and machine learning models for demand prediction.

    Jupyter Notebook