
Data Science with AI
Data Science with AI explores how modern AI tools—particularly Large Language Models (LLMs)—can supercharge the work of data professionals. This course demonstrates how AI can be leveraged to accelerate, automate, and enhance data analysis, from query generation and code writing to advanced visualization and storytelling. Participants will gain hands-on exposure to cutting-edge tools that are reshaping the data science workflow. The course features live demonstrations using:
- ChatGPT for generating and explaining SQL, R, and Python code
- Microsoft Office Copilot for AI-powered spreadsheet analysis
- Google Colab for working with Python and integrating ChatGPT APIs
- Microsoft Power BI (focusing on M and DAX)
- Tableau for dynamic AI-augmented data visualization
Whether you’re cleaning data, building dashboards, or automating reports, this course will show how AI can make your work faster, smarter, and more impactful.
Duration
½ day
Audience
This course is designed for data analysts, data scientists, developers, and other professionals who want to integrate AI into their data workflows to boost productivity and innovation.
Prerequisites
Participants should have a working knowledge of data analysis fundamentals, including SQL, Python, and spreadsheets. A basic familiarity with visualization tools such as Power BI, Tableau, or matplotlib is also recommended. No prior AI experience is required.
Is there a discount available for current students?
UMBC students and alumni, as well as students who have previously taken a public training course with UMBC Training Centers are eligible for a 10% discount, capped at $250. Please provide a copy of your UMBC student ID or an unofficial transcript or the name of the UMBC Training Centers course you have completed. Asynchronous courses are excluded from this offer.
What is the cancellation and refund policy?
Student will receive a refund of paid registration fees only if UMBC Training Centers receives a notice of cancellation at least 10 business days prior to the class start date for classes or the exam date for exams.