100538 - Virginia Tech Data Analytics Bootcamp

Overview

The Virginia Tech Data Analytics Bootcamp is designed for students to pursue high-quality tech education while continuing to balance work or other commitments. Our program provides you with the flexibility to fit career development into your life.

After 144 hours of synchronous instruction, participants will learn:

• Business Analytics with Excel: Gained a deep understanding of the advanced features of Excel, including conditional formatting, analyzing data with pivot tables, statistics, macros, and Power Query
• SQL: Data Acquisition and Manipulation: Designed and applied the Structured Query Language (SQL) for database definition and manipulation in databases and tables, utilizing operators, constraints, and data types; JOINs, set operators, and subqueries; and window functions and views
• ETL (Extract, Transform, and Load) Data Processes: Integrated data from multiple sources into one data set to prepare it for storage, utilizing AWS Glue; data source identification, extraction, and transformation; and ETL tools and technologies
• Data Visualization Using Tableau: Explored Tableau to create and optimize interactive data visualizations using charts, dashboards, and stories; complete data preparation, filtering, and analytics; and other advanced Tableau capabilities
• Fundamentals of Python Programming: Learned to use Python to build and manage data structures, including conditional statements, loops, and functions; and object-oriented programming (OOPs) and threading
• Data Analytics with Python: Applied Python programming toward analyzing, wrangling, and visualizing data, including linear algebra, statistics, data analysis, wrangling, and visualization; use of Python libraries included NumPy and Panda
• Essentials of Generative AI: Gained generative AI skills using top tools like ChatGPT and Google Gemini; investigated Genai functionality, prompt engineering, and ethics; and AI use cases for data analysis and storytelling
• Applications of Generative AI in Data Analytics: Explored how to use AI in data analytics to aid data discovery, exploration, and visualization, utilizing ETL and data modeling automation, and AI transformation in data visualization
• Ethics in Data Analytics: Explored the ethical implications of data practices—from privacy and consent to data bias, understanding the legal frameworks and data privacy, informed consent principles, and the ethical obligations of data professionals

The learners can gain the ability to:

• Use advanced features and formulas in Microsoft Excel
• Create presentations using data storytelling techniques and visualizations
• Design, learn, and apply SQL for database definition and manipulation
• Apply Python fundamentals to manipulate and analyze data
• Use AWS Glue to apply ETL (Extract, Transform, Load) processes

Visit our website to learn more.