Data Analytics Foundations
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Data Analytics Foundations
This course is part of DeepLearning.AI Data Analytics Professional Certificate
Instructor: Sean Barnes
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Skills you'll gain
- Requirements Analysis
- Business Requirements
- Spreadsheet Software
- LLM Application
- Data Literacy
- Exploratory Data Analysis
- Data Visualization Software
- Business Analytics
- Large Language Modeling
- Analytical Skills
- Requirements Elicitation
- Analytics
- Data-Driven Decision-Making
- Data Presentation
- Data Analysis
- Data Visualization
- Data Storytelling
- Statistical Visualization
Tools you'll learn
Details to know
See how employees at top companies are mastering in-demand skills
Build your Data Analysis expertise
- 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 DeepLearning.AI
There are 4 modules in this course
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.
This course is the first in a series designed to prepare you for an entry level data analyst role. You don’t need any prior experience with analytics software, programming, or even data to succeed in this course. Whether you’re looking to start a career in data analytics or level up in your current role, this course is for you. It’s designed to take you from no prior experience to leading your own end to end projects. And, if you’re already working as a data analyst or in a similar role, you’ll find new strategies and insights to continue growing in your career. Starting out, you’ll learn what data is & the many forms it can take. Then, you’ll get hands on with spreadsheets, a powerful tool for analyzing and visualizing data. You’ll explore real-world datasets throughout the video demos and the interactive labs, including hotel bookings, baby names, and home sales. Finally, you’ll learn a structured approach for data analytics projects that works across industries. Plus, throughout this course, you’ll get hands-on with large language models, which are changing the nature of work. They are not a replacement for your perspective, but they can augment your skills, serving as a thought partner for your practice. In this course, you’ll use LLMs to interpret data visualizations, run analyses, and more. Data analytics is both analytical and creative. While you will crunch numbers, and that’s fun in its own right, you’ll also craft compelling stories to inspire action. You’ll discover new things every day, work with people from all backgrounds, and see the real world impacts of your expertise.
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 videos7 readings7 assignments1 ungraded lab
20 videos•Total 82 minutes
- Welcome to data analytics!•6 minutes
- Generative AI in this course•3 minutes
- Module 1 introduction•1 minute
- Life as a data analyst•4 minutes
- What is data analytics?•5 minutes
- Evidence-based decision-making•6 minutes
- A history of data analytics•4 minutes
- Modern industry use cases•5 minutes
- Defining data•3 minutes
- Unstructured data•4 minutes
- Structured data•5 minutes
- Big data•5 minutes
- Data ecosystems•3 minutes
- Collaborators outside your data team•4 minutes
- Collaborators on your data team•4 minutes
- Introduction to large language models•4 minutes
- Choosing an LLM•3 minutes
- Prompting LLMs•3 minutes
- LLM limitations•5 minutes
- Demo: Interacting with LLMs•6 minutes
7 readings•Total 117 minutes
- Welcome to the course•5 minutes
- Join the DeepLearning.AI Forum to ask questions, get support, or share amazing ideas!•1 minute
- Data in ancient civilizations•10 minutes
- About the LLM Labs in this course•10 minutes
- Graded Lab: Pizza delivery•80 minutes
- Module 1 resources•10 minutes
- Module 1 lecture notes•1 minute
7 assignments•Total 120 minutes
- Lesson 1 quiz•10 minutes
- Lesson 2 quiz•10 minutes
- Practice Lab: E-commerce sales•20 minutes
- Lesson 3 quiz•10 minutes
- Lesson 4 quiz•10 minutes
- Module 1 quiz•30 minutes
- Graded Lab: Pizza delivery insights quiz•30 minutes
1 ungraded lab•Total 45 minutes
- Practice Lab: LLMs for data & decision-making•45 minutes
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 videos11 readings5 assignments1 ungraded lab
19 videos•Total 89 minutes
- Module 2 introduction•1 minute
- Solving problems with data•3 minutes
- Spreadsheets for business analytics•3 minutes
- Navigating Google Sheets•6 minutes
- Importing data•5 minutes
- Sorting, filtering, and formatting•4 minutes
- Getting to know your data•3 minutes
- Summary statistics - MAX, MIN, AVERAGE•5 minutes
- Conditional formatting•6 minutes
- Summary statistics – COUNTIF•3 minutes
- Summary statistics– SUMIF, AVERAGEIF•4 minutes
- Summary statistics – COUNTIFS, SUMIFS•6 minutes
- Data processing – IF, IFS, RIGHT, LEFT•5 minutes
- Where does data come from?•5 minutes
- Data exploration with LLMs•6 minutes
- Introduction to time series•6 minutes
- Real-world time series•4 minutes
- Moving averages•7 minutes
- Percent change•6 minutes
11 readings•Total 226 minutes
- Accessing Google Sheets and its alternatives•20 minutes
- Working with spreadsheets in this course•10 minutes
- Named ranges•10 minutes
- Cells and cell ranges•10 minutes
- Practice Lab: Exploring the Hotel Reservations dataset•30 minutes
- LLMs and privacy•15 minutes
- Choosing the right LLM approach•10 minutes
- Practice Lab: Exploring baby names•30 minutes
- Graded Lab: Video game market research•80 minutes
- Module 2 resources•10 minutes
- Module 2 lecture notes•1 minute
5 assignments•Total 80 minutes
- Lesson 1 quiz•10 minutes
- Lesson 2 quiz•10 minutes
- Lesson 4 quiz•10 minutes
- Module 2 quiz•30 minutes
- Graded Lab: Video game market research insights quiz•20 minutes
1 ungraded lab•Total 30 minutes
- Practice Lab: Using an LLM for data exploration•30 minutes
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 videos7 readings6 assignments1 ungraded lab
17 videos•Total 78 minutes
- Module 3 introduction•1 minute
- What is data storytelling?•5 minutes
- The language of data visualizations•6 minutes
- Analyzing visualizations•6 minutes
- The right chart for the right insight•6 minutes
- Demo: Bar & column charts•5 minutes
- Demo: Customizing charts•4 minutes
- Demo: Scatter plots•4 minutes
- Demo: Grouped bar & column charts•4 minutes
- Demo: Stacked bar & column charts•3 minutes
- Demo: Line charts•2 minutes
- Strategies for effective data visualization•6 minutes
- Data encoding•5 minutes
- Chart elements•5 minutes
- Data visualization examples: the good and the better•7 minutes
- Demo: Interpreting data visualizations with LLMs•5 minutes
- Demo: Creating data visualizations with LLMs•4 minutes
7 readings•Total 181 minutes
- Chart types & insights•20 minutes
- Additional chart types and insights•20 minutes
- Practice Lab: Exploring hotel reservations•30 minutes
- Graded Lab: Bike sharing market research•80 minutes
- Book references•20 minutes
- Module 3 resources•10 minutes
- Module 3 lecture notes•1 minute
6 assignments•Total 90 minutes
- Lesson 1 quiz•10 minutes
- Lesson 2 quiz•10 minutes
- Lesson 3 quiz•10 minutes
- Lesson 4 quiz•10 minutes
- Module 3 quiz•30 minutes
- Graded Lab: Bike sharing market research insights quiz•20 minutes
1 ungraded lab•Total 30 minutes
- Practice Lab: Data visualization with LLMs•30 minutes
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 videos9 readings6 assignments1 ungraded lab
14 videos•Total 52 minutes
- Module 4 introduction•1 minute
- The data analytics lifecycle•5 minutes
- Defining the problem•3 minutes
- Collecting & preprocessing data•5 minutes
- Analyzing data•4 minutes
- Identifying insights•2 minutes
- Sharing results•4 minutes
- Evaluating outcomes•4 minutes
- Gathering stakeholder requirements•4 minutes
- Synthesizing stakeholder input•5 minutes
- Checking in with stakeholders•5 minutes
- Domain knowledge•2 minutes
- Demo: LLMs for stakeholder analysis•7 minutes
- Your next steps in data analytics•1 minute
9 readings•Total 251 minutes
- Alternate versions of the data analytics lifecycle•20 minutes
- Understanding the Rumsfeld Matrix•10 minutes
- Domain knowledge examples•15 minutes
- Practice Lab: Spotify case study•30 minutes
- Graded Lab: Bakery case study•80 minutes
- Module 4 resources•10 minutes
- Module 4 lecture notes•1 minute
- Capstone: Customer cancellation analysis•80 minutes
- Acknowledgments•5 minutes
6 assignments•Total 130 minutes
- Lesson 1 quiz•10 minutes
- Lesson 2 quiz•10 minutes
- Spotify case study quiz•10 minutes
- Module 4 quiz•30 minutes
- Graded Lab: Bakery case study insights quiz•40 minutes
- Capstone: Maven Analytics churn analysis insights quiz•30 minutes
1 ungraded lab•Total 30 minutes
- Practice Lab: LLMs for stakeholder analysis•30 minutes
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Reviewed on Oct 30, 2025
This was the most engaging and value packed online course I have attended. Thank Sean Barnes for being a very good online instructor/facilitator. I loved every moment of this program.
Reviewed on May 4, 2025
Very comprehensive and thorough coverage of the foundations, data story telling and visualizations. I enjoyed this learning session and super value add.
Reviewed on Jun 16, 2025
The course is well designed and in easy-to-understand method for beginners.
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