| Title | Associated Subject | Mentor/University | Description | Year | Project Details |
|---|---|---|---|---|---|
| Predictive Analytics using Artificial Intelligence & ML | Business Process Analytics | Dr. Javier Rubio-Herrero University of North Texas |
In this project, a research study is conducted on Young Presidents Organizations (YPO) to predict the churn in a case when a subscriber shifts to a competitive company. The study utilizes a data set from YPO that contains information on consumer membership status. The study includes geographical and historical details of consumers, like region, current membership status, tenure, etc., to predict the renewal status of a potential member. A preliminary step includes conducting an exploratory data analysis on the data set. Further, a machine learning model is created and trained with the data set. In terms of the technical environment, Automated Machine Learning (AutoML) is used to create data pipelines to fetch data from the cloud and trains model on the Azure cloud. The model utilizes the Binary Model and classification techniques to derive the test results of the YPO case study. In addition, analytics Microsoft Analytics tool Power BI is used to depict the insights derived from the ML model results. In a nutshell, this project is a demonstration, with the help of a YPO case study, of how a real-world $40.7 billion industry works on intelligent methods and makes strategies based on ML model insights. * Developed an AI & Machine Learning based model to conduct predictive analytics for customer trends for Business Analytics * Predicted model with 99.22% accuracy using ML methods Classification, Regression, Binary & conducted analytics using Azure, PowerBI | Jan-May 2022 |
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| Big Data Analytics Project | Big Data Analytics | Prof Scott Hamilton University of North Texas |
This subject focuses on the applications of Big Data. | Jan-May 2022 |
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| Data Visulaization Project | Data Visualization | Prof Russell Torres University of North Texas |
This subject walks through the various data visualization tools and practices. The project comprised of generating visualizations via Tableau. | Jan-May 2022 |
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| Cryptocurrency Forecast using Data Mining | Data Mining & Machine learning | University of North Texas |
* Developed a data mining project to predict the trend of multiple Cryptocurrencies using SAS Enterprise Miner & SAS studio * Predicted 91% of cryptocurrencies will be at least triple-fold in the next 10 years suggested by Segmentation & Classification models | Aug-Dec 2021 |
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| Qunatum Computing Applications in Data Science | Enterprise Applications of Business Intelligence | Dr.Tony Girth University of North Texas |
The solutions to the most complex problems are usually found in the fundamental basic principles. In the 21st decade, technology has reached new heights, and curiosity to find the answers has explored all its boundaries. The data that has been consumed over the 30 years before the internet era is now produced only in a single day. This exponential increase in data production and analysis has given birth to the most advanced technologies, and it led to the invention of Quantum Computing. Quantum Computing is a classic combination of physics, computer science, and statistics to make supercomputers to solve the complex equations that any human mind can think about. The applications of data sciences that will use the results of quantum computing have a tremendous potential to change the analytics world. | Aug-Dec 2021 |
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| Tableau Analytics for Global Superstores | Accounting Management | Prof Neil Wilner University of North Texas |
This class is dedicated to data visulaization and analytics via Tableau. Global Superstore has incorporated the loss of $9.2 million and loss of $2.8 million alone in the Technology category in the duration of 2011 to 2015. The problem being investigated is the effect of shipment modes on profits. We believe, the problem exists in the Machine subcategory and in the shipment of machines via First class which has caused a loss in profits. Machinery is usually bulky and fragile, and its expensive transportation via First class has declined the profits. In nutshell, we believe, Global Superstore has lost profit in Technology category majorly due to First Class shipment mode of Machines. | Aug-Dec 2021 |
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| Project | Marketing Management | Prof Kenneth N. Thompson University of North Texas |
This subject involves working through the case studies and evaluating marketing strategies. This case studies are evaluated usining analytics nad financial analysis of the firm. This comprises evaluating case studies of Americana's Hotel, Breeder's Own Pet Food, Burrough's Wellcome, Crafton Industies, Haverwood Furnitures, South Delaware Colors and Zoecon to evaluate their marketing and financial strategy. | Jun-Aug 2021 |
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| Project | Model-Based Business Intelligence | Dr. Hakan Tarakci University of North Texas |
This subject focuses on the depth of Model-Based Business Intellignce Applications. It involves working through the ML models and deriving valuable insights. | Jan-May 2021 |
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| Uber Market Share Case Study | Organizational Behavior | Dr. Virginie Lopez-Kidwell University of North Texas |
This subject walks through the principles of Organizational Behaviors and work through various case studies. * Worked on evalauting Uber Market Share Case Study * Managed as an acting PM for SDLC based Uber Case Study Research for launching new products using agile and waterfall methodizes * Analyzed the deployment & success of products, and recommended agile and waterfall strategies for short- & long-term design features | Jan-May 20121 | Project Details |
| Project | Financial Mangement | Prof Tomas Mantecon Prieto University of North Texas |
This subject walks through the principles of financial management. | Jan-May 2021 | |
| Business Decisions using Statistical Techniques | Business Decision Process | Prof Hakan Tarakci University of North Texas |
This subject focuses on dervining business decisions using statistical techniques for industrial applications. * Developed a predicted-based model to predict snowfall in North Americas in 2020 using Z-distribution, statics & regression techniques * Predicted a hypothesis of 20% increased snowfall in 2020 with key inferences with a 95% Confidence Interval by validating p and t values | Aug-Dec 2021 |
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