The purpose of this repository is to organize, track and showcase my data-related projects. It also contains exercises solved in my fun time from different platforms and open challenges like avent of code, exercism, statascratch and so on.
- advent of code subdirectory : avent of code
- python exercism-tracks subdirectory : python track exercises
- sql exercism-tracks subdirectory : sql track exercises
- other sources : leetcode, statascratch, etc
- random exercises
Project : Accenture Virtual Experience - Data Analytics and Visualization
Description : This project involves identifying the client’s business problem based on the brief and datasets provided, it also involved use of the ETL (Extract, Transform and Load) process. I also created a dashboard with several visualizations using Power BI in order to get insights, make my analysis and give my recommendations.
Tech Stack : Python, Pandas, Numpy, Seaborn, Matplotlib, SciPy.
Skills: Business and Data understanding, ETL, statistical data analysis, data visualization.
Description : This project involves exploring the data as an analyst and creating a digital based solution for the home loan department of standard bank using machine learning algorithms to improve processing time and prediction of a loan applicant’s eligibility.
Tech Stack : Python, Scipy, , Numpy.
Skills: Business and Data understanding, ETL, statistical data analysis, data visualization.
Project : Visual Perception - Segmentation and Depth Estimation Networks
Description : The project involves the implementation of a segmentation network to classify desired road participants on a pixel-based level and also the implementation of a depth estimation network for estimating the depth (distance) of road objects in images and video data using Python, Pytorch and its related libraries.
Tech Stack : Python, Numpy, Pandaas, Matplotlib, OpenCV, Pytorch, Pytorch Ligthning.
Skills: Computer vision, Image processing, Neural Networks, Data Science.
Project : Goldman Sachs Virtual Experience - Excel Business Project
Description : This project involves the creation forecast operating assumptions for the client’s revenue, costs and cashflow, translated the set of forecasted assumptions and used it to build the profit and loss (P&L) forecast statements. Utilized the cash flow assumptions alongside the P&L forecast to complete the cash flow analysis and used the forecasted cash flow analysis to calculate a closing cash balance for each period. Creating output charts in excel to show insights on how the business will perform over the next 5 years.
Tech Stack : Python, Pandas, Numpy, Seaborn, Matplotlib, SciPy.
Skills: Business and Data understanding, ETL, statistical data analysis, data visualization.
Project : Applications of Neural Network Models in Kaggle Competition
Description : This project involves the exploration of Kaggle Datasets ( MNIST, Malaria Cell Classification and Kvasir Endoscopic Images) and application of neural network algorithms on these data. It also explores the mathematics behind these algorithms, the optimization of the hyperparameters of the networks and comparison of different optimization algorithms on these networks.
Tech Stack : Python, Numpy, Pandas, Matplotlib, OpenCV, Pytorch, Pytorch Ligthning.
Skills: Computer vision, Image processing, Neural Networks, Data Science, Data Analysis, Data visualization.
Project : Data Analytics Project - Predictive Monitoring andOptimization of Transport and Logistic Processes
Description : This project involves working in a team to predict the delivery time for a particular freight transportation process and also determine which processes are important business using statistical and machine learning methods.
Tech Stack : Python, Pandas, Numpy, R.
Skills: Business and data understanding, ETL, statistical data analysis, dimensionality reduction, machine learning (ML) techniques, regression analysis, data visualization.
Project : [ Bachelor Thesis - Optimization of a Manufacturing Company’s Profit using Linear Programming]
Description :
Skills: Linear programming, sensitivity analysis, mathematical methods, data collection, data cleaning, data analysis, public speaking, optimization.