Civil Engineering Data

Education

University of Colorado Boulder

M.S in Computer Science, GPA 4.00 Graduation: Dec 2019

M.S in Civil Engineering, GPA 3.80 Graduation: May 2018

B.S. in Civil Engineering, GPA 3.63 Graduation: Dec 2015

Completed Classes: Machine Learning, Object-Oriented Design, Software Management, Algorithms, Data Structures, Operating Systems, Computer System

Current Classes: Datacenter Scale Computing, Data Mining

Skills

•Proficient: Python, C++, SQL

•Familiar with: C, Java, CSS, HTML

•Data Science and Engineering: Pandas, Numpy, scikit-learn, TensorFlow, Hadoop, Spark

Courses

Machine Learning CSCI 5622 – University of Colorado Boulder Jan – May 2018

•Solved various real-life problems using different algorithms and classifiers which include K-Nearest Neighbors, Logistic Regression, Feature Engineering, Boosting and Neural Networks in Python.

•Created a project with a team to classify humorous pictures and train a model to produce comedic content to explore computational humor using Convolutional Neural Networks and Recurrent Neural Network.

•Analyzed multiple datasets obtained from researching different data sources and filtered through thousands of data entries to ensure viable training datasets and to improve accuracy in outcome.

Object-Oriented Design CSCI 5448 – University of Colorado Boulder Jan – May 2018

•Built an online educational portal system software using Django Framework, MySQL, and HTML.

•Followed specific design patterns and Object-Oriented Principles which were implemented in Java and Python.

Projects

Team member, Colorado Data Science Team – Boulder, Colorado Aug 2018 - Present

•Build a project with a team to solve a real-life problem supervised by CU Boulder Professors.

•Participate in internal competitions (CU Boulder), and external competitions (e.g. Kaggle, Netflix).

Data Science Projects – Self May 2018 – Present

•Created an image-classifier following Michael Nielsen’s book on Neural Networks to classify handwritten digits.

•Built a movie recommendation model utilizing lightfm Python Library that provides recommendation algorithms and data extraction methods to build the model.

•Used Spark to build a neural network model and a Naïve Bayes models to classify different types of irises, and built scripts to preprocess textual and numerical data to use for different models.

SQL Projects – Self July 2018 – Sept 2018

•Used SQL queries to build and modify a database of customer orders on Microsoft SQL Server.

•The database included tables for products, customers, and orders. The order table combined data entries from customers and products.

•Created a company database that includes tables for employees, managers, branches, orders, clients and suppliers.

•Utilized SQL queries to retrieve information, using combinations of foreign keys, unions, and wildcards.

Work Experience

Computer Science Tutor, University of Colorado Boulder – Boulder, Colorado March 2017 – Aug 2018

•Tutored sophomore students Data Structures and Algorithms.

•Taught C++, Python and various concepts that include Hash Maps, Binary Trees, and Graphs.

•Assisted students in debugging their projects and assignments in Python and C++ and prepared them for exams.

Teacher Assistant, CVEN 4606 CU Boulder – Boulder, Colorado Jan 2016 - June 2016

•Assisted the professor in carrying out class strategy through assignments and graded weekly student assignments.

•Communicated with students regarding their mistakes and explained concepts taught in class.

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