Certificate in Data Analytics

This introductory course offers a practical overview of data analytics, covering the three primary analytics categories: descriptive, predictive and prescriptive.. Students learn the data analysis process, from asking questions to presenting insights—while building data literacy through basic statistics and visualization. Hands-on activities with Microsoft Excel develop skills in data manipulation, formulas, functions and charting. Real-world examples reinforce learning, and ethical considerations like data privacy and integrity are introduced. By the end, learners are prepared to progress to SQL, statistics and dashboarding in subsequent certificate courses.

This course introduces data management and SQL for querying relational databases, core skills for data analysts. Students learn to design simple data models, retrieve and combine data using SQL and perform basic data cleaning and transformation. Through hands-on practice, they develop skills in writing queries for selection, aggregation and joins. By working with real-world datasets, students gain the ability to extract and prepare data for analysis in tools like Excel or visualization platforms.

This course introduces fundamental statistics and probability concepts essential for data analysis. Students learn to describe data, make inferences and assess reliability using methods like confidence intervals, hypothesis testing and regression. Emphasis is placed on practical application using tools like Excel, with accessible math and real-world examples such as A/B testing and survey analysis. By the end, students will be able to apply statistical reasoning to support sound, data-driven decisions.

This course introduces students to business intelligence (BI) tools for visual analytics. Students learn to use Tableau and Power BI to connect data sources, create dashboards and communicate insights. We focus on simulating business scenarios and developing visualizations that support decision-making.

This course introduces students to advanced data analysis capabilities in Excel, Tableau and Power BI. Students explore features such as forecasting, automation and emerging AI-assisted tools to increase efficiency and insight generation. Python is introduced at a conceptual level to show how it supports data workflows without requiring programming.

This course focuses on translating data into compelling narratives for business audiences. Students learn how to structure data stories, select effective visuals and present findings clearly and ethically. Final assignments emphasize integrating analysis and communication.