I like math adjacent fields.
Degrees and Certificates
Master’s of Science in Business Analytics | 2017
Graduate Certificate of Basic Business Foundations | 2017
Bachelors of Science in Information Technology | 2014
Minor in Mathematical Sciences and Computer Science | 2014
Graduate Course Work
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ACCT 7000 |
FIN ACCT FOUNDATION |
Fall Semester 2015-16 |
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A course that was an introduction to accounting. The accounting equation was covered. | |
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BA 7000 |
MKTS & ORGS |
Fall Semester 2014-15 |
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Course where we analysed different company case studies such as McDonalds and Harley. | |
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BANA 6025 |
OPTIMIZATION MODELS |
Spring Semester 2014-15 |
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Course where we used Excel Solver and AMPL to solve optimization problems. We covered linear and non-linear optimization. | |
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BANA 6026 |
OPT METHODS |
Spring Semester 2014-15 |
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Course where we dived more into the logic and math behind optimization as well as using the tool GAMS. | |
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BANA 6035 |
SIMULATION MODELING |
Fall Semester 2015-16 |
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Course where we used Arena Simulation Tool to simulate real life situation such as queues, call centers, and other things. We used probability models to pull wait times and customer throughput.
Final Project: Simulating Apache Web Server traffic load and comparing different methods of load balancing such as Least Connections, Round Robin, etc. |
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BANA 6037 |
DATA VISUALIZATION |
Spring Semester 2014-15 |
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Course where we used Tableau to visualize different types of data and learn why certain colors, lines and other visual elements should be included or avoided. | |
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BANA 6043 |
STATISTICAL COMPUTING |
Spring Semester 2017 |
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Course where we used R and SAS for basic statistical functions and data cleansing. | |
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BANA 7031 |
PROBABILITY MODELS |
Fall Semester 2017 |
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Course where we studied events, probability spaces and probability functions; Random variables; Distribution and density functions; Joint distributions; Moments of random variables; | |
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BANA 7041 |
STATISTICAL METHODS |
Fall Semester 2014-15 |
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Nonlinear regression and generalized linear model | |
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BANA 7042 |
STAT MODELING |
Spring Semester 2015-16 |
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Basic estimation, hypothesis testing, and data analysis. Point and interval estimation. One factor ANOVA. SAS |
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BANA 7046 |
DATA MINING I |
Spring Semester 2017 |
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This is a course in the statistical data mining with emphasis on hands-on data analysis experience using various statistical methods and major statistical software (SAS and R) to analyze large complex real world data. Topics include: Data Processing. Variable Selection for linear regression and generalized linear regression. Out-of-sample Cross Validation. Generalized Additive models. Nonparametric smoothing methods. Classification and Regression Tree. Neural Network. Monte Carlo Simulation | |
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BANA 7047 |
DATA MINING II |
Spring Semester 2017 |
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Continuation of Data Mining I |
Projects
2017 Graduate Capstone
In 2015, The University of Cincinnati began to transition its Student Information System from a homegrown system to a system created by Oracle Peoplesoft called Campus Solutions and branded by UC as Catalyst. In order to perform reporting and analytics on this data, the data must be extracted from the source system, modeled and loaded into a data warehouse. The data can then be exported to perform analytics. In this project, the process of extract, modeling, loading and analyzing will be covered. The goal will be to predict students’ GPA and retention for a particular college.
2014 Senior Project
The Sitter App is an Android application designed for those who utilize others to look after their children and pets. Currently, parents give paper notes to the sitter, which wasteful, may leave helpful information out, or be illegible. The Sitter App uses built-in mobile functionality to make information easier to access regarding the child or pet. Profiles are created for each child or pet by the parent and are temporarily sent to the sitter. Profiles can include rules, discipline, routine, interests, allergies, phone numbers and other information pertinent to the sitter. Updates can also be sent to the parent from the sitter in order to update parent on routine. The parent no longer has to worry that they may have left out information for the sitter and the sitter no longer has to call the parent for small issues or questions, creating a better experience for sitter, parent and child.