Rahul Agre

Highly motivated and detailed-oriented candidate passionate about using data to improve business performance and customer experience. Skilled at leveraging data to develop actionable solutions to business challenges and utilizing data mining and data visualization to create meaningful insights. Excellent technical aptitude and knowledge of python programming language, data analytics and data visualization.

B.E. Final Year Project

The main goal of this project is to describe a technological solution to automatically characterize the quality of yarn using Image Processing techniques. The proposed solution enables measurement of the hair length index.

Executive PG Programme in Data Science (Deep Learning), IIITB Project

The problem statement chosen for this project is to predict fraudulent credit card transactions with the help of machine learning models.

In this project, you will analyze customer-level data which has been collected and analyzed during a research collaboration of Worldline and the Machine Learning Group

The dataset is taken from the Kaggle website and it has a total of 2,84,807 transactions, out of which 492 are fraudulent. Since the dataset is highly imbalanced, so it needs to be handled before model building.

Github link is mentioned below.

https://github.com/RahulAgre/CC_FraudDetection_Capstone

BCG Data Science Job Simulation on Forage:

• Business Understanding & Hypothesis Framing
• Exploratory Data Analysis
• Feature Engineering & Modelling
• Findings & Recommendations

British Airways Virtual Data Science Internship on Forage:

• Scraping and collecting customer feedback by analyzing third-party data.
• Presenting my insights using PowerPoint.
• Preparing the dataset.
• Training a machine learning model.
• Evaluating and presenting my findings.

Accenture Nordics Developer Virtual Programme on Forage:

• Architecture: Define technical requirements. Design changes to an existing architecture. Scale on-premise system infrastructure to the cloud.
• Programming: Reading and understanding code. Attention to detail. Debugging algorithms.
• Testing: Unit testing. User Acceptance Testing - UAT.
• Security: Security maturity assessment. IAM policies and permissions. Securing the software development lifecycle (SDLC).
• Artificial Intelligence: Shaping the Problem. Data and privacy.

Data Analysis and Visualization with Python by IBM.

IBM Cloud Essentials.

Interskill AIX(UNIX) System Administrator - Fundamentals by IBM.