Introduction to Data Analytics

Instructor: Anke Audenaert

Beginner Level • 2 weeks at 10 hours a week • Flexible Schedule

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

Skills You'll Gain

Data Collection
Data Quality
Data Validation
Analytics
Data analysis
Data Visualization
Key Performance Indicators (KPIs)
Business Metrics
Generative AI
Data Manipulation
Data Modeling
Data Storytelling
Data Cleansing
Exploratory Data Analysis

Shareable Certificate

Earn a shareable certificate to add to your LinkedIn profile

Outcomes

  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate from Meta

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.

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.

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.

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.

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.