This course provides a practical understanding and framework for basic analytics tasks, including data extraction, cleaning, manipulation, and analysis. It introduces the OSEMN cycle for managing analytics projects and you'll examine real-world examples of how companies use data insights to improve decision-making.
Introduction to Data Analytics
This course is part of multiple programs.
Instructor: Anke Audenaert
Sponsored by Southeastern University
61,362 already enrolled
(567 reviews)
Recommended experience
What you'll learn
Apply the data analysis process OSEMN to marketing data
Compare and contrast various data formats and their applications across different scenarios
Identify data gaps and articulate the strengths and weaknesses of collected data
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There are 5 modules in this course
This week, you will learn what data analytics are and what a data analyst does. You’ll be introduced to the OSEMN framework as well as important business metrics, KPIs and their value to a business.
What's included
13 videos5 readings3 assignments
In the second week you will learn how to discover different sources of data and how to evaluate their validity. You will also explore different data formats. You’ll begin to apply the OSEMN framework by learning the steps in the data cleaning process as well as how to handle missing or incorrect data in your datasets.
What's included
16 videos3 readings4 assignments
This week moves onto the Exploring and Modeling phases of OSEMN. You will learn how to inspect and summarize your data as well as evaluate data relationships. You will discover the purpose of data modeling and common types of data models and data visualizations.
What's included
15 videos2 readings4 assignments
This week you will learn how to interpret the data you have working with and relate the results of your analysis back to a specific business goal. You will also learn how to create a story for a presentation of your data in order to explain and engage an audience.
What's included
15 videos1 reading5 assignments
In this optional module, you learn what generative AI is and how it functions. You also discover how GenAI can be applied in different business scenarios as well as navigating the concerns around its usage. Then you explore how to incorporate GenAI into your data analytics efforts to streamline processes and improve data quality.
What's included
8 videos4 readings3 assignments1 discussion prompt
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