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DeepLearning.AI

Data Storytelling

DeepLearning.AI via Coursera

Overview

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In this course, you’ll learn to communicate insights in ways that drive real decisions. You’ll explore how to choose the right format to present your findings and tailor your message to technical and non-technical audiences. You’ll start by learning how to craft data stories that provide context and align with business goals. Then, you’ll apply those skills by designing clear, effective charts that highlight a single insight. Next, you’ll build interactive dashboards in Tableau using features like annotations, tooltips, and “Show Me.” These skills transfer easily to tools like Power BI and Looker Studio. In the final module, you’ll prepare for the job search: analyzing roles, tailoring your resume and portfolio, building your network, and getting ready for interviews. Throughout the course, you’ll practice applying these skills to realistic business scenarios so you’re ready to share insights that influence decisions.

Syllabus

  • Data storytelling fundamentals
    • This module explores the art and strategy of data storytelling, an essential skill for communicating insights effectively in business and technical contexts. You'll learn how data storytelling differs from traditional reporting by focusing on narrative, context, and audience engagement. Through hands-on practice, you'll develop data stories with a clear arc, highlight key findings, and tailor your message to different formats including memos, dashboards, notebooks, and slide decks. You'll also learn how to document your work clearly with elements like data sources, refresh dates, and version control to build trust and transparency with stakeholders.
  • Creating charts with Tableau
    • This module introduces the principles of effective data visualization and reporting using Tableau. You’ll begin by creating a Tableau Public account and building your first workbook. Then, through guided practice and scenario-based exercises, you’ll learn to choose the right type of insight and visualization—such as line charts, heat maps, or geographic plots—to match your audience and goals. You’ll also explore how to write clear summaries that highlight key findings and support decision-making. Finally, you'll apply design best practices for color, typography, and layout, including how to align with brand guidelines to create visually consistent and impactful reports.
  • Creating dashboards & stories with Tableau
    • In this module, you'll build a strong foundation in data visualization and dashboard creation, with a focus on using Tableau effectively. You’ll start by exploring key features of Tableau and other common visualization tools, then move on to best practices in dashboard design and delivery formats such as subscriptions, scheduled reports, and interactive dashboards. You'll gain hands-on experience connecting to data from one or more tables, using joins and unions, and distinguishing between dimensions and measures. You’ll also perform data transformations with basic calculations and field edits. To support the design process, you’ll create mock-ups and wireframes, and then bring them to life by building a variety of static and interactive visualizations in Tableau—ranging from bar and pie charts to tree maps and dual-axis maps. Finally, you’ll add filters and tooltips, optimize dashboard performance, and deploy your work to ensure accessibility across platforms.
  • The Job Search
    • This module guides you through the key stages of the job search process, from identifying opportunities to succeeding in interviews. You'll learn to interpret job listings, distinguish between hard and soft requirements, and apply strategies for finding roles that align with your skills. You'll explore the importance of networking and how to build professional connections both online and in person. The module also covers optimizing your LinkedIn profile, crafting resumes with strong bullet points and formatting, and creating a compelling portfolio that highlights your data analytics work. You’ll leverage generative AI tools to tailor application materials and practice interview techniques using the STAR method and simulation tools—preparing you to confidently pursue a career in data analytics.

Taught by

Sean Barnes

Reviews

4.8 rating at Coursera based on 31 ratings

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