Course Overview 

The Data Analytics Essentials Short-Term Course offers an introduction to the foundational concepts, tools, and techniques used in data analysis. With data playing a central role in decision-making across industries, this course helps learners explore how raw data can be processed into valuable insights using structured methods.

Participants will be introduced to key areas of data analytics, including data types, data cleaning, exploratory data analysis, and basic data visualization. The course covers essential tools such as Microsoft Excel, SQL, and introductory concepts in Python or R, offering a balanced mix of theory and practical application.

This course is structured to build data literacy and analytical thinking. While it provides hands-on exposure to real-world data scenarios, it does not guarantee any specific career or academic outcomes. Instead, it serves as a stepping stone for learners interested in understanding how to interpret and communicate data-driven findings.

Designed for students, working professionals, and curious learners from any background, the course provides a flexible and accessible approach to learning analytics basics in a simplified, beginner-friendly format.

What will students learn in your course? 

• Understand the role and process of data analytics in real-world contexts
• Learn types of data, data formats, and basic data cleaning methods
• Explore tools like Excel, SQL, and introductory Python/R functions
• Practice basic data visualization using charts, graphs, and dashboards
• Interpret datasets using descriptive statistics and trends
• Understand the basics of data-driven decision making
• Learn how to frame and explore analytical questions
• Work with simple datasets for hands-on practice

Requirements / Prerequisites 

• Basic computer literacy is essential to navigate analytical tools and online learning platforms used in the course.
• No advanced programming or statistics background is required; the course is designed for beginners with a general interest in data.
• Learners must have access to a computer or laptop with internet connectivity to complete lessons and practical exercises.

Who is this course for?

• Students from any discipline curious about working with data
• Non-technical professionals seeking data interpretation skills
• Entry-level individuals interested in analytics fundamentals
• Business or research professionals exploring data-informed thinking