The University of Texas at Austin
Data Analysis and Visualization Certificate | Jul 2020 - Jan 2021
My name is Cedric Vanza and this is my Portfolio webpage.
Thank you for visiting!
I am a Data Analyst, an efficient and reliable professional with experience in data source projects and excellent track record transforming data into
results.
You may consider checking the projects listed here by clicking on the menu Projects above or just scrolling down the page.
My resume is available on the menu above as well.
Once more, I would like to thank you for visiting
this portfolio.
Python, R, SQL, NoSQL, HTML5, CSS3, Git, Bootstrap, JavaScript, JSON, Plotly, D3, Tableau, PySpark
This project used ETL techniques and Python Scikit-Learn to analyze Austin car crash data from 2018 to 2020 and created an interactive dashboard using a Random Forest Classifier algorithm to predict a driver score from user's features.
Code Live Demo Tableau DashboardThis project builds a TensorFlow Neural Network to analyze hand-written digit images and predict the digit or the class of the input image.
CodeThis project uses TensorFlow and deep learning neural networks to analyze and classify the success of charitable donations.
Code
This project focuses on building a dynamic webpage that accepts user inputs and adjusts accordingly to display information about UFO sightings.
In order to perform their analysis, users will be able to filter the UFO sightings
table based on multiple criteria such as the event date, city, state, country and shape.
This project uses unsupervised machine learning, PCA algorithm, and K-Means clustering to analyze and classify a database of cryptocurrencies.
CodeAnalyze and visualize PyBer 2019 ride-sharing data using Python, Pandas and Matplotlib, to help the company improve access to ride-sharing services and determine affordability for underserved neighborhoods.
CodeR programming language, statistics and hypothesis testing to analyze a series of datasets from the automotive industry.
CodeThis project analyzes Amazon Vine program and determines if there is a bias toward favorable reviews from Vine members. The analysis uses PySpark to perform the ETL process to extract the dataset, transform the data, connect to an AWS RDS instance, load the transformed data into pgAdmin and calculate different metrics.
CodeThis project builds and evaluates several machine learning algorithms to predict credit risk.
CodeData Analysis and Visualization Certificate | Jul 2020 - Jan 2021
M. Sc. Eng. Higher Education, Electronic Communications
B.S. Engineering