Data Analytics

Students will graduate with a solid understanding of the mathematical and statistical concepts that form the foundation of data analytics. They will comprehend regression analysis, central tendency measures, probability, and hypothesis testing—all crucial instruments for precise data interpretation and analysis.

Students will acquire the skills necessary to gather, purify, arrange, and prepare unprocessed data from a variety of sources. This involves practical knowledge of programs like Excel and SQL, which enable students to efficiently handle organized datasets prior to incorporating them into analytical models.

In data analytics, students will learn at least one programming language, usually R or Python. These languages will teach them how to do statistical analysis, work with data, and build simple machine learning models.

Through the use of Tableau, Power BI, and Python libraries like Matplotlib and Seaborn, the program teaches students how to produce insightful and engaging data visualizations. Students will gain the capacity to convert intricate data insights into understandable graphics for stakeholder or company communication.