Ziyuan Xu

Master's Degree in Applied Computer Science. Extensive experience with practical applications including database, software development, Machine Learning. Skilled at data collecting, preprocessing and analysis. Detail-oriented team player seeking opportunities as a data analyst, software engineer or general office support worker.

Google Data Analytics Professional Certificate

• Completed extensive three months job-ready Google Career Certificate training. Demonstrated hands-on experience with data cleaning and visualization , project management , interpreting and communicating data analytics findings. Solid understanding of database with fluency in tools like Google sheet , Tableau .

Atlassian Agile with Atlassian Jira

• Completed Agile with Atlassian Jira training. Learned Agile methodologies including Kanban and Scrum systematically. Applied agile practices, created and managed agile boards in Jira Software Cloud .

AWS Cloud Technical Essentials

• Completed AWS Cloud Technical Essentials training. Studied terminology and concepts related to AWS services including Amazon EC2 , AWS security measures and AWS Identity and Access Management ( IAM ). Explored Amazon DynamoDB and Amazon S3 .

Microsoft Azure Developer Associate

• Completed Microsoft Azure Developer Associate (AZ-204) Professional Certificate Training. Learned how to implement Azure compute solutions , manage web apps, develop solutions utilizing Azure storage, implement authentication and authorization.

IBM Python for Data Science and AI

• Completed Python for Data Science and AI and development training. Delved into collecting data by the use of API s and webscraping .

Data Analysis for LOL, 09/2022 - 12/2022

St. Francis Xavier University, Antigonish NS 

• Analyzed League of Legends dataset on Jupyter Notebook . Conducted preprocessing and removed all irrelevant attributes with SQL . Visualized the data using bar chart, line chart, pie chart, word cloud, and heat map. Summarized the factors making contributions to winning the game. Predicted the results with SVM and Random Forest. Achieved a prediction accuracy of more than 96%.

Knowledge-Point Annotation, 01/2020 - 07/2021

Zhengzhou University, China 

• Adopted Spring Boot framework, implemented a text annotation system by Java and HTML file. Delivered to NLP Lab of Information Engineering School of Zhengzhou University for teaching and research. Applied for Computer Software Copyright Registration in the name of university as the main author.