Timeline
Work History
Skills
Summary
Certification
Projects
Manager
CHANDRA SEKHAR P

CHANDRA SEKHAR P

DATA SCIENCE
TIRUPATI

Timeline

Machine Learning Intern

IBM Smartinternz
08.2022 - 11.2022

Work History

Machine Learning Intern

IBM Smartinternz
08.2022 - 11.2022
  • Identified new problem areas and researched technical details to build innovative products and solutions.
  • Developed advanced graphic visualization concepts to map and simplify the analysis of heavily-numeric data and reports.
  • Studied new technologies to support machine learning applications.
  • Transformed raw data to conform to assumptions of the machine learning algorithm.

Skills

  • PYTHON
  • EXPLORATORY DATA ANALYSIS
  • MACHINE LEARNING
  • TABLEAU
  • HTML
  • MY SQL
  • GIT AND VERSION CONTROL

Summary

  • An aspiring software engineer with knowledge in software engineering practices such as coding, testing, code reviews, code comments, etc. Strong ability to communicate with clients and ability to express ideas clearly and concisely.

Certification

  • Data Science with python (06/2022- 08/2022)
    Simplilearn - IBM
  • Data Scientist with Python (08/2020- present)
  • Data Camp Certified Data scientist (05/2022- 09/2022) Simplilearn - IBM
  • Machine Learning (09/2022- 10/2022) Naan Mudhalvan - Infosys Springboard
  • Machine Learning and Deep Learning course (07/2022- Present) Stanford university online - Course

Projects

  • Chronic kidney disease detection using Machine Learning (08/2022 - 11/2022)
    A virtual internship project provided by SmartInternz in collaboration with IBM.
    used python libraries like NumPy and pandas for exploratory data analysis and matplotlib and seaborn for data
    visualization.
    used the Scikit-learn library for developing machine learning models.
  • Customer request analysis using Data Science (02/2022 - 04/2022)
    Analyzed NYC 311 customer request data to develop insights on customer behaviour and trends
    Implemented statistical methods and developed a machine learning model.
    Used NumPy, Pandas libraries for exploratory data analysis and matplotlib and seaborn for data visualization.
    Used the scikit-learn library to build a machine learning model.
  • Retail Analysis with Walmart Data (03/2022 – 05/2022)
    Project Based on Retail Analysis with Walmart Data
    Using linear regression and variables like dates, we have built a prediction model to forecast demand for certain
    products. Also, to hypothesis if CPI, unemployment, and fuel prices have any impact on sales.
  • Investigating Netflix Movies and Guest Stars in The Office
    Dig into a real-world Netflix movie dataset using everything from lists and loops to pandas and matplotlib.
    Implemented statistical methods and developed a machine learning model.
    Used NumPy, Pandas libraries for exploratory data analysis and matplotlib and seaborn for data visualization.
    Used the scikit-learn library to build a machine learning model.

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CHANDRA SEKHAR PDATA SCIENCE