Interactive Course

Data Science for Business Leaders

Learn about data science and how can you use it to strengthen your organization.

  • 4 hours
  • 14 Videos
  • 51 Exercises
  • 16,539 Participants
  • 3,350 XP

Loved by learners at thousands of top companies:

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Course Description

What is data science and how can you use it to strengthen your organization? This course will teach you about the skills you need on your data team, and how you can structure that team to meet your organization's needs. Data is everywhere! This course will provide you with an understanding of data sources your company can use and how to store that data. You'll also discover ways to analyze and visualize your data through dashboards and A/B tests. To wrap up the course, we'll discuss exciting topics in machine learning, including clustering, time series prediction, natural language processing (NLP), deep learning, and explainable AI! Along the way, you'll learn about a variety of real-world applications of data science and gain a better understanding of these concepts through practical exercises.

  1. 1

    Introduction to Data Science

    Free

    We'll start the course by defining what data science is. We'll cover the data science workflow, and how data science is applied to real-world business problems. We'll finish the chapter by learning about ways to structure your data team to meet your organization's needs.

  2. Analysis and Visualization

    In this chapter, we'll discuss ways to explore and visualize data through dashboards. We'll discuss the elements of a dashboard and how to make a directed request for a dashboard. This chapter will also cover making ad hoc data requests and A/B tests, which are a powerful analytics tool that de-risk decision-making.

  3. Data Collection and Storage

    Now that we understand the data science workflow, we'll dive deeper into the first step: data collection. We'll learn about the different data sources your company can draw from, and how to store that data once it's collected.

  4. Prediction

    In this final chapter, we'll discuss the buzziest topic in data science: machine learning! We'll cover supervised and unsupervised machine learning, and clustering. Then, we'll move on to special topics in machine learning, including time series prediction, natural language processing, deep learning, and explainable AI!

  1. 1

    Introduction to Data Science

    Free

    We'll start the course by defining what data science is. We'll cover the data science workflow, and how data science is applied to real-world business problems. We'll finish the chapter by learning about ways to structure your data team to meet your organization's needs.

  2. Data Collection and Storage

    Now that we understand the data science workflow, we'll dive deeper into the first step: data collection. We'll learn about the different data sources your company can draw from, and how to store that data once it's collected.

  3. Analysis and Visualization

    In this chapter, we'll discuss ways to explore and visualize data through dashboards. We'll discuss the elements of a dashboard and how to make a directed request for a dashboard. This chapter will also cover making ad hoc data requests and A/B tests, which are a powerful analytics tool that de-risk decision-making.

  4. Prediction

    In this final chapter, we'll discuss the buzziest topic in data science: machine learning! We'll cover supervised and unsupervised machine learning, and clustering. Then, we'll move on to special topics in machine learning, including time series prediction, natural language processing, deep learning, and explainable AI!

What do other learners have to say?

Devon

“I've used other sites, but DataCamp's been the one that I've stuck with.”

Devon Edwards Joseph

Lloyd's Banking Group

Louis

“DataCamp is the top resource I recommend for learning data science.”

Louis Maiden

Harvard Business School

Ronbowers

“DataCamp is by far my favorite website to learn from.”

Ronald Bowers

Decision Science Analytics @ USAA

Mari Nazary
Mari Nazary

VP of Content at DataCamp

Mari Nazary is a global EdTech executive who partners with educators and subject matter experts to build and scale effective, outcomes-focused, SaaS learning solutions. After spending over a decade working in EdTech for multimillion dollar brands and startups, Mari knows what truly closes the skills gap across the world—and it’s not mastering the marketing flavor of the week. It’s how well you understand your learners’ needs in order to help them measure and achieve real-world success. Mari has designed digital learning solutions for worldwide audiences including Rosetta Stone, EF Education First, and DataCamp. In addition to her instructional design and curriculum development expertise, Mari is a certified Agile scrum master, Python programmer, and data analyst. Mari holds an MA in Linguistics from Middlebury College and a BA from Barnard College in Classics.

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Michael Chow
Michael Chow

Assessment Research Lead at DataCamp

Michael is a data scientist at DataCamp, where he develops models for adaptive assessment. He has programmed in python and R for a little over a decade, and received a PhD in cognitive psychology from Princeton University. His research interests include statistical methods, skill acquisition, and human memory. You can follow him on twitter @chowthedog.

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kaelen medeiros
kaelen medeiros

Data Scientist, Product at DataCamp

Kaelen is the Data Scientist for the Product team at DataCamp. They are an admin for the R-Ladies Global community. Kaelen received a MS in Biostatistics from Louisiana State University Health Sciences Center, where they worked at the Louisiana Tumor Registry. Before DataCamp, they designed experiments (and more!) for the American College of Surgeons, HERE Technologies, and HealthLabs. If you meet them, you will undoubtedly hear about their cat, Scully, within the first 3 minutes. Other favorite topics include aliens, popcorn, podcasts, and nail polish.

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Ramnath Vaidyanathan
Ramnath Vaidyanathan

VP of Product Research at DataCamp

Ramnath Vaidyanathan is the VP of Product Research at DataCamp, where he drives product innovation and data-driven development. He has 10+ years experience doing statistical modeling, machine learning, optimization, retail analytics, and interactive visualizations. He brings a unique perspective to product development, having worked in diverse industries like management consulting, academia, and enterprise software. Prior to joining DataCamp, he worked as a data scientist at Alteryx, leading the roadmap for interactive visualizations and dashboards for predictive analytics. Prior to Alteryx, he was an Assistant Professor of Operations Management in the Desautels Faculty of Management at McGill University. His research primarily focused on the application of predictive analytics and optimization methodologies to improve operational decisions in retailing. He got his Ph.D. in Operations Management from the Wharton School.

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Collaborators
  • Amy Peterson

    Amy Peterson

  • Hillary Green-Lerman

    Hillary Green-Lerman

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