Skills

Mathematics

CalculusMatrix and Linear AlgebraProbabilityStochastic Processes

Statistics

Statistical LearningStatistical AnalysisData VisualizationTime Series
Statistical InferenceNonparametric StatisticsRegression AnalysisSurvey Methods

Computer Science

Artificial IntelligenceDatabase ManagementWeb ApplicationsSoftware Engineering

Python

  • Use python for data cleaning, exploratory data analysis, visualization, statistics, machine learning, deep learning, error analysis, and present the results using Jupyter Notebooks, Markdown and dashboards
  • Pandas
  • NumPy
  • Matplotlib
  • Seaborn
  • Scikit-learn
  • TensorFlow
  • SciPy

R

  • Use R for data cleaning, exploratory data analysis, visualization, statistics, machine learning, and present the results using R Markdown and dashboards
  • dplyr
  • ggplot2
  • tidyr
  • packages for machine learning

Tableau

  • Blend and join data from multiple sources
  • Create data visualizations with corresponding tools
  • Apply functions to extract insights from data
  • Create calculation fields to perform advanced calculations
  • Use parameters to create interactive visualizations
  • Present the results using dashboards
  • interact between different visualizations in dashboard by actions

JavaScript

  • Node.js (For backend server)
  • React (For frontend web applications)

SQL (MySQL, Oracle)

  • Data cleaning: remove duplicates, filter and sort data, transform data, and validate data integrity
  • Data manipulation: select and retrieve data from tables, join tables, and aggregate data using functions by SQL queries
  • Data modeling: create and modify database structures, including tables, indexes, and constraints
  • Interaction: Use other tools, such as Python, JAVA, Tableau, to access the database, select and retrieve data by SQL queries

NoSQL (MongoDB)

JAVA

C

SAS

Excel