Let's start with the importance of data storytelling and the elements you need to tell stories with data. You'll learn best practices to influence how decisions are made before learning how to translate technical results into stories for non-technical stakeholders.


Fundamentals of storytelling

The story begins

Building a story

Translating technical results

A non-tech story

Be aware

Impacting the decision-making process

Is it a true story?

Structured to impact

A story to compare

Storytelling with Data

Deepen your storytelling knowledge. Learn how to avoid common mistakes when telling stories with data by tailoring your presentations to your audience. Then learn best practices for including visualizations and choosing between oral or written formats to make sure your presentations pack a punch!


Selecting the right data

The truth about salaries

Earning interests

Showing relevant statistics

Salary variation

On a payroll

It's not significant

Visualizations for different audiences

Salary development

Salary on demand

Choosing the appropriate format

A communication problem

Should we meet?

When in doubt

Preparing to Communicate the Data

Now that you understand how to prepare for communicating findings, it’s time to learn how to structure your reports. You'll also learn the importance of reproducibility (work smarter, not harder) and how to get to the point when describing your findings. You’ll then get to apply all you’ve learned to a real-world use case as you create a compelling report on credit risk.


Types of reports

Data Science Report

Something to report

Options

Final report

Summary report

In summary

Reproducibility and references

Replicate me

Bad practice

Best practice

Same results

Write precise and clear reports

Improvable

Intelligible

Half-empty glass

Strong words

Case study: report on credit risk

Credit me

Summary Report

Report my credit

Structuring Written Reports

You'll finish by learning simple techniques to structure a presentation, communicate insights, and inspire your audience to take action. Lastly, you'll learn how to improve your communication style and prepare to handle questions from your audience.


Planning an oral presentation

Is this the plan?

An effective plan!

Building presentation slides

A color building

Too much text

The right building

Delivering the presentation

Put it into practice

Avoiding common errors

The true mistake

Do's and don'ts

Congratulations!

Building Compelling Oral Presentations

You’ve analyzed your data, run your model, and made your predictions.  Now, it's time to bring your data to life! Presenting findings to stakeholders so they can make data-driven decisions is an essential skill for all data scientists. In this course, you’ll learn how to use storytelling to connect with your audience and help them understand the content of your presentation—so they can make the right decisions. Through hands-on exercises, you’ll learn the advantages and disadvantages of oral and written formats. You’ll also improve how you translate technical results into compelling stories, using the correct data, visualizations, and in-person presentation techniques. Start learning and improve your data storytelling today.

The videos contain live transcripts you can reveal by clicking "Show transcript" at the bottom left of the videos.									
The course glossary can be found on the right in the resources section.
									
To obtain CPE credits you need to complete the course and reach a score of 70% on the qualified assessment. You can navigate to the assessment by clicking on the CPE credits callout on the right.									

<h2>Learn the Basics of Data Communication</h2> 
<br>
You’ve analyzed your data, run your model, and made your predictions. Now, it's time to bring your data to life! Presenting findings to stakeholders so they can make data-driven decisions is an essential skill for all data scientists. In this course, you’ll learn how to use storytelling to connect with your audience and help them understand the content of your presentation—so they can make the right decisions. 
<br><br>
<h2>Explore Formats of Data Communication</h2> 
<br>
Through hands-on exercises, you’ll learn the advantages and disadvantages of oral and written formats. You’ll also improve how you translate technical results into compelling stories, using the correct data, visualizations, and in-person presentation techniques. Start learning and improve your data storytelling today.

Understanding Data Science

Understanding Data Visualization

No one enjoys looking at spreadsheets! Bring your data to life. Improve your presentation and learn how to translate technical data into actionable insights. 

Data Communication Concepts

Yardımcı Veri Analisti SQL içinde

Yardımcı Veri Bilimcisi in R

Yardımcı Veri Bilimcisi  Python'da

Before you start analyzing the data, open the dataset in a text editor to delete all unwanted columns.

For your machine learning model, do not set the random seed argument as it will always return the same result, eliminating randomness.

Erase intermediate files created from your machine to avoid confusion.

Use a Jupyter notebook, so you can explain your thought and decision-making process at each step of the analysis.

Create an extra file where you write down the Python packages and versions you use for the analysis.

Use a software to handle references so you can correctly cite the sources you consult during the project work.

Same results

Data Communication Concepts

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