Data and AI Courses
Basic Data Analytics
This course introduces learners to the fundamentals of working with data to answer questions and support decision‑making. The course covers essential topics such as data types, data collection, cleaning and preparation, basic statistics, and introductory data visualization. Using common tools, students learn how to explore datasets, identify patterns, and communicate insights clearly, building a strong foundation for more advanced study in data or analytics.
Advanced Data Analytics
This advanced course builds on foundational skills to equip learners with deeper analytical and technical expertise. It focuses on advanced statistical methods, machine learning techniques, predictive and prescriptive analytics, and data modeling using large or complex datasets. Students work with professional tools to design, evaluate, and deploy analytical solutions, while also learning to interpret results, manage uncertainty, and communicate insights strategically to support data‑driven decisions in real‑world contexts.
Data Analytics Tools
This course focuses on building practical skills with the software and platforms commonly used by data professionals. Learners gain hands‑on experience with tools for data cleaning, analysis, and visualization—such as spreadsheets, SQL databases, and business intelligence or analytics platforms. The course emphasizes selecting the right tool for a task, efficiently working with real datasets, and presenting insights clearly, enabling students to confidently apply analytics tools in academic, business, or professional settings.
Working with Microsoft Power BI
This hands-on course teaches learners to transform raw data into clear, interactive, and impactful visual insights using Microsoft Power BI. The course covers connecting to multiple data sources, cleaning and modeling data, creating dashboards and reports, and using DAX for basic calculations. Emphasis is placed on best practices for data visualization and storytelling, enabling students to confidently use Power BI to analyze data, share insights, and support data‑driven decision‑making in professional environments.
Data Visualization
This course teaches learners how to present data clearly and effectively through visual representations that support understanding and decision‑making. The course covers principles of visual design, chart selection, color usage, and storytelling with data, along with hands‑on practice using common visualization tools. Students learn how to transform complex datasets into intuitive charts and dashboards, communicate insights to diverse audiences, and avoid common pitfalls that can mislead or confuse viewers.
Data Storytelling
This course focuses on turning data insights into clear, compelling narratives that inform and persuade audiences. Learners explore how to combine data analysis, visualizations, and contextual framing to craft stories that highlight key findings and support decision‑making. The course emphasizes audience awareness, structure, and clarity, helping students communicate complex data in a way that is engaging, meaningful, and actionable for both technical and non‑technical stakeholders.
Using R Programming
This course introduces learners to data analysis and statistical computing with the R programming language. The course covers core concepts such as data import and cleaning, exploratory data analysis, basic statistics, and data visualization using popular R packages. Through hands‑on exercises and real‑world datasets, students learn how to write reproducible analyses, interpret results, and effectively communicate insights, building a strong foundation for work in data analytics, research, or data science.
AI Essentials
This AI Essentials course introduces learners to the core concepts and practical foundations of artificial intelligence. It covers topics such as what AI is, how machine learning works at a high level, common AI applications, and the benefits and limitations of AI systems. The course also emphasizes ethical considerations, responsible use, and real‑world examples, helping students develop a clear, non‑technical understanding of how AI impacts organizations, industries, and everyday life.
Working with Microsoft Copilot
This is a practical course that teaches learners how to use Microsoft Copilot to enhance productivity, creativity, and decision‑making across everyday work tasks. The course explores how Copilot integrates with Microsoft 365 applications such as Word, Excel, PowerPoint, Outlook, and Teams to assist with writing, data analysis, summarization, and collaboration. Emphasis is placed on effective prompting, responsible use of AI, and real‑world scenarios, enabling participants to confidently leverage Copilot as an intelligent work assistant.