In this course, you’ll learn to harness the volume & complexity of information to help businesses make better decisions. This is data analytics, and it powers insights across almost every industry, even ones you might not think of: from fashion and government, to tech, sports and healthcare.



Data Analytics Foundations
This course is part of DeepLearning.AI Data Analytics Professional Certificate

Instructor: Sean Barnes
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24 assignments
March 2025
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There are 4 modules in this course
This module introduces key concepts in data analytics, focusing on data types, formats, roles, and the ecosystem surrounding data. It explores various data representations, differentiates between types of data, and introduces common data file formats. Additionally, it delves into the responsibilities of different data roles and career opportunities in the field. The module also covers the strengths and weaknesses of large language models (LLMs) and their applications in data analytics.
What's included
20 videos6 readings7 assignments1 ungraded lab
This module provides a practical guide to using spreadsheets effectively, both in everyday life and in a business context. It covers the foundational skills needed to operate spreadsheets, particularly Google Sheets. You will explore various use cases, learn how to address different business problems with specific data types, and gain hands-on experience with essential spreadsheet tasks. It also includes a comparison of file types and their connection to structured and unstructured data, as well as techniques for organizing and analyzing data within spreadsheets.
What's included
19 videos10 readings5 assignments1 ungraded lab
This module delves into the art of data visualization, a crucial skill for data analysts to effectively communicate insights and drive decision-making. You will learn the role of visualizations in data storytelling, explore various graph and chart types, and develop the ability to create and interpret visual data representations. The module emphasizes best practices for selecting the most appropriate visualization for different analyses. You will also look at using LLMs to help interpret and create data visualizations.
What's included
17 videos6 readings6 assignments1 ungraded lab
This module provides a detailed exploration of the data analysis lifecycle, emphasizing the systematic approach required to turn raw data into actionable insights. You will learn about each stage of the lifecycle—from defining the problem to evaluating the effectiveness of decisions—and how to gather business context and stakeholder requirements to refine business questions. The module also covers the process of determining the appropriate type of analysis, the impact of domain knowledge, and tools like the Rumsfeld Matrix to ensure comprehensive analysis and decision-making.
What's included
14 videos8 readings6 assignments1 ungraded lab
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