Sorry, this page is no longer available

We may earn an affiliate commission when you visit our partners.

From Data to Decisions

Getting Started with AI

William Doyle

4.1

Based on 11 ratings

, see reviews

William Doyle

This course is intended for individuals who'd like to work with data from their organization but don't know where to start. We'll combine generative AI and your insights to structure research questions, understand the variables in your dataset, and begin describing the data for the purpose of generating insights into better decisions. After taking this course, learners will know how to identify the outcomes and predictors in a dataset and how to summarize different types of variables in a dataset using generative AI.

Enroll now

Or subscribe to Coursera Plus

And get unlimited access to Coursera

Two deals to help you save

Save money when you learn. Here are two deals and offers that may be relevant to this course.

All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.

Valid until July 14

Coursera Plus Annual

Work toward what's next for your career with access to 10,000+ programs. Discover emerging skills and save.

Valid until August 30

Google AI App Builder

Learn how to use Gemini API and API Studio with a three-course series from Google DeepMind

What's inside

Syllabus

Getting Started With Data Analysis

Types of Variables

Describing Variables Using Generative AI

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Combines generative AI with user insights, which helps learners structure research questions and understand variables, even without prior experience

Focuses on identifying outcomes and predictors in a dataset, which is a foundational skill for anyone starting in data analysis

Teaches how to summarize different types of variables using generative AI, which is a modern approach to data exploration

Presented by Vanderbilt University, which is known for its programs in data science and quantitative methods

Save this course

Create your own learning path. Save this course to your list so you can find it easily later.

Save

Reviews summary

Getting started with data and ai

Learners say this course provides an excellent introduction to using AI for data analysis, making it ideal for those new to data. Many found the explanations clear and easy to follow, particularly the sections on types of variables and using generative AI to describe data. The hands-on exercises were frequently praised as very practical. However, a few reviewers noted the course felt a bit too simplistic and lacked depth, particularly on the "decision-making" aspect, suggesting it's more focused on data description with AI rather than full analysis leading to complex decisions. Some also wished the AI tool part went deeper.

Explains fundamentals like variable types.

"Good overview, especially the section on types of variables."

"I loved how it broke down variable types."

"It provides a solid foundation, covering variable types well."

Using generative AI for data description.

"The hands-on exercises were very practical and helped me understand how to apply generative AI tools."

"Using AI to summarize data felt very modern and relevant."

"The generative AI part was good for quick summaries."

Excellent starting point for beginners.

"This was an excellent introduction to using AI for data analysis."

"Explanations were really clear, even for someone new to data."

"As a complete beginner, this was perfect! Easy to follow..."

AI section could go deeper.

"Found the AI tool part useful, although sometimes it felt a bit surface-level."

"The AI section was basic prompts, not deep insight."

"...the AI integration is a nice touch, though I agree with others it could go deeper."

Not enough focus on decision-making.

"I was hoping for more depth on actual decision-making frameworks..."

"It felt a bit too simplistic. Expected more rigor in the data analysis part."

"The 'decisions' part felt missing. It's more 'Data to Description using AI'."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in From Data to Decisions: Getting Started with AI with these activities:

Review Basic Statistics Concepts

Show steps

Reviewing basic statistical concepts will provide a solid foundation for understanding data analysis techniques used in the course.

Browse courses on Descriptive Statistics

Show steps

Review measures of central tendency (mean, median, mode).
Review measures of dispersion (variance, standard deviation).
Practice calculating basic statistics using sample datasets.

Review 'Naked Statistics: Stripping the Dread from the Data'

Show steps

Reading 'Naked Statistics' will help you understand the underlying statistical principles behind data analysis and AI.

View Naked Statistics: Stripping the Dread from the... on Amazon

Show steps

Read the book, focusing on chapters related to descriptive statistics.
Take notes on key concepts and examples.
Reflect on how these concepts relate to the course's focus on data-driven decision-making.

Create a Glossary of Data Analysis Terms

Show steps

Creating a glossary will reinforce your understanding of key data analysis terms and concepts covered in the course.

Show steps

Identify key terms from the course materials.
Define each term in your own words.
Provide examples of how each term is used in data analysis.
Organize the terms alphabetically for easy reference.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Practice Identifying Variable Types

Show steps

Practicing identifying variable types will solidify your understanding of this fundamental concept in data analysis.

Show steps

Find datasets online (e.g., Kaggle, UCI Machine Learning Repository).
For each dataset, identify the different variables.
Classify each variable as either categorical or numerical.
Further classify numerical variables as discrete or continuous.
Further classify categorical variables as nominal or ordinal.

Review 'Storytelling with Data: A Data Visualization Guide for Business Professionals'

Show steps

Reading 'Storytelling with Data' will help you improve your data visualization skills and communicate your findings more effectively.

View Storytelling with You: Plan, Create, and... on Amazon

Show steps

Read the book, focusing on chapters related to data visualization best practices.
Analyze examples of effective and ineffective data visualizations.
Apply the principles learned to your own data visualization projects.

Analyze a Public Dataset and Summarize Findings

Show steps

Analyzing a real-world dataset will allow you to apply the concepts learned in the course and develop your data analysis skills.

Show steps

Choose a public dataset that interests you.
Identify potential research questions that can be addressed using the data.
Summarize the variables in the dataset using descriptive statistics.
Use generative AI to help you interpret the results and generate insights.
Write a brief report summarizing your findings.

Create a Data Visualization Dashboard

Show steps

Creating a data visualization dashboard will allow you to present your data analysis findings in a clear and compelling way.

Show steps

Choose a dataset that you have analyzed.
Identify key insights that you want to communicate.
Select appropriate visualizations to represent your data (e.g., bar charts, scatter plots, line graphs).
Create a dashboard using a data visualization tool (e.g., Tableau, Power BI).
Add interactive elements to allow users to explore the data.

Career center

Learners who complete From Data to Decisions: Getting Started with AI will develop knowledge and skills that may be useful to these careers:

Data Analyst

A data analyst examines data to identify trends, patterns, and insights that support business decisions. The work of a data analyst centers around the skills taught in this course, such as structuring research questions, understanding variables, and describing them using generative artificial intelligence. This course teaches how to identify predictors and outcomes in datasets, a core component of the data analyst's toolset. Those who wish to become a data analyst may find this course most helpful.

See salaries and explore the career path for Data Analyst

Business Analyst

A business analyst uses data analysis to improve organizational practices and decision-making. This role benefits from an understanding of how to structure research questions and how to understand and describe variables using tools such as generative artificial intelligence, as this course teaches. The work of a business analyst involves working with datasets and the ability to identify predictors and outcomes. This course helps one become proficient with data analysis and aids in structuring research using artificial intelligence.

See salaries and explore the career path for Business Analyst

Market Research Analyst

A market research analyst interprets data on consumer behavior and market trends to inform business strategies. This role requires the ability to understand and summarize data, including identifying key predictors and outcomes, which aligns with the skills this course provides. Market research analysts need to develop research questions and describe variables using tools such as generative artificial intelligence, which makes this course very useful. Market research involves working with varied datasets, and the skills taught in this course help in describing those to generate actionable insights.

See salaries and explore the career path for Market Research Analyst

Research Associate

A research associate conducts research and analyzes data to support projects in various fields. The skills covered in this course, such as structuring research questions, describing variables using generative artificial intelligence, and identifying predictors and outcomes in a dataset, are fundamental to this role. A research associate might need to summarize different types of variables in datasets to support primary research. This course may be useful for those who wish to be research associates and who have an interest in working with data.

See salaries and explore the career path for Research Associate

Operations Analyst

An operations analyst uses data to improve the efficiency and effectiveness of business operations. This role requires the ability to work with data, understand variables, and generate insights for better decisionmaking, all of which this course provides a foundation for. The course is particularly helpful in creating research parameters and using generative artificial intelligence to describe data. An operations analyst may find this course useful as operations requires the analysis of complex datasets.

See salaries and explore the career path for Operations Analyst

Intelligence Analyst

An intelligence analyst collects and analyzes data to produce actionable insights for organizations, often in the fields of security or business. The role of an intelligence analyst involves research and interpretation of data, which is precisely what this course teaches with its focus on structuring research questions, understanding variables, and using generative artificial intelligence for description. For an intelligence analyst, the ability to identify predictors and outcomes in datasets and summarize them is key, and this course may be helpful.

See salaries and explore the career path for Intelligence Analyst

Consultant

A consultant works with clients to solve business problems, often involving data analysis and research. The course teaches how to structure research questions, which is a critical skill for a consultant. Consultants must be able to describe variables using generative artificial intelligence and understand predictors and outcomes in datasets. This course can help one become more effective in a consultant role, particularly when working with data-driven projects, and it may be useful for those who wish to enter that field.

See salaries and explore the career path for Consultant

Policy Analyst

A policy analyst uses data to evaluate and recommend policies for governments or organizations. A policy analyst uses a structured and methodical approach to research, much of which involves the use of data. This course may be useful to policy analysts because it teaches how to summarize, describe, and identify variables and outcomes in datasets using generative artificial intelligence. This can lead to insights that inform better policy recommendations.

See salaries and explore the career path for Policy Analyst

Project Manager

A project manager oversees projects from initiation to completion, often involving the collection and analysis of project data. To be effective, a project manager must understand project outcomes and predictors, aligning with concepts taught in this course. This course introduces how to structure research questions and describe variables using generative artificial intelligence, which may be useful for project managers looking to use data in a project's life cycle. This course can help a project manager gain insights from project data.

See salaries and explore the career path for Project Manager

Data Scientist

A data scientist uses advanced statistical and machine learning techniques to analyze large datasets and solve complex problems. While this course does not focus on the advanced skills of a data scientist, it provides a foundational understanding of how to structure research questions, how to understand and describe variables, and how to identify predictors and outcomes in a dataset. It also introduces the use of generative artificial intelligence. This may be helpful to someone who wishes to become a data scientist by introducing them to core data analysis concepts.

See salaries and explore the career path for Data Scientist

Research Scientist

A research scientist conducts scientific research in various fields, often involving data analysis and experimentation. This course may be useful to research scientists by providing an introduction to the basics of data analysis and generative artificial intelligence to describe variables, and to structure research questions. Those in this role might also find it beneficial to understand how to identify predictors and outcomes in a dataset, which is taught in this course. Much scientific research involves data gathering and organization, which is core to this course.

See salaries and explore the career path for Research Scientist

Financial Analyst

A financial analyst examines financial data to inform investment decisions and strategies. While not a primary focus, the ability to structure research questions and describe variables using generative artificial intelligence, as taught in this course, can be a benefit to a financial analyst. It may also be useful for a financial analyst to be able to identify predictors and outcomes within datasets. This course may help a financial analyst gain a deeper understanding of data.

See salaries and explore the career path for Financial Analyst

Statistician

A statistician applies statistical methods to collect, analyze, and interpret data. Though this course is not focused solely on statistical methods, it may be useful to a statistician because it teaches the basics of data analysis, how to identify predictors and outcomes, and how to describe different types of variables using generative artificial intelligence. This course may be useful for a statistician to understand how generative artificial intelligence can be used in the early stage of data analysis.

See salaries and explore the career path for Statistician

Actuary

An actuary uses statistical data to assess risk and probability, primarily for insurance companies. This course may be useful because it covers methods for analyzing data and identifying outcomes and predictors as well as describing vaiables using generative artificial intellignece. A course that teaches basic data analysis may be useful for someone looking to go into an actuarial field. However, much of actuary work involves advanced statistical principles not covered by this course.

See salaries and explore the career path for Actuary

Database Administrator

A database administrator manages and maintains organizational databases. Although the work of a database administrator is focused on the structure and maintenance of databases, a database administrator may find it beneficial to understand how data is interpreted. The ability to identify predictors and outcomes as well as to describe variables using artificial intellignece may be useful for a database administrator. This course provides an introduction to those concepts; therefore, it may be useful.

See salaries and explore the career path for Database Administrator

Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in From Data to Decisions: Getting Started with AI.

Storytelling with You

Save

Focuses on the art of communicating data effectively through visualizations. It provides practical guidance on how to choose the right visuals, design clear and compelling charts, and tell a story with your data. It useful reference tool for anyone who wants to improve their data visualization skills. This book adds more depth to the existing course.

Storytelling with You: Plan, Create, and Deliver a...

Paperback

Storytelling with You: Plan, Create, and Deliver a...

Kindle Edition

Naked Statistics

Save

Provides an accessible and engaging introduction to statistical concepts. It explains complex ideas in a clear and intuitive way, making it ideal for learners with limited statistical backgrounds. It helps to demystify statistics and build confidence in working with data. This book is more valuable as additional reading than as a current reference.

Naked Statistics: Stripping the Dread from the Data

Paperback

NEW-Naked Statistics

Paperback

Naked Statistics: Stripping the Dread from the Data

Kindle Edition

Help others find this course page by sharing it with your friends and followers: