Communicating and Visualizing Data
From November 16 to November 20 (Online)
Communicating and Visualizing Data module is focused on exploring the data visualization field through computational design approaches and information and communication theory.
By attending the course, the participants will learn to develop visual, interactive and web-based projects that make raw data perceivable through digital experiences and are able to communicate value and insights to different stakeholders (from manager to executives, from tech people to generic audience).
The training is an intensive learn-by-doing process featuring hands-on activities and team work.
About the importance of Data Visualization
Today Data Visualization is a critical component in different fields: Applied Data Science, Industry 4.0, design and communication, journalism, civic technologies.
Furthermore, DataViz must be considered as a key tool in working with any type of data during the entire project lifecycle, from the exploration phase, through the hypothesis validation, to the presentation of the results.
In today’s competitive world, having technical proficiency is sometimes not enough to drive an organization towards an impactful data-driven transformation. Designing an effective narrative and mastering communication skill are critical to achieve competitive results. This module aims to combine information theory and communication skills with a deep knowledge of specific graphic computational tools.
Is this course for me?
This course is mainly designed for all the people that are interested in deepening the comprehension and the methodologies related to visualizing and communicating the value of a dataset or of a data-driven project.
Some examples of candidates who might be a perfect match are:
- People with a solid background in graphic design who want to dive into an immersive computational design journey and to create interactive web-based visualizations
- UI / UX practitioners and software developers (mainly frontend) who want to add the Data Visualization skill to their toolbox
- Journalists and humanists who are not afraid to write code to create visual data storytelling
- Data scientists or data analyst who want to add to their belt the tools and the mindset to generate dashboards and to create compelling “from data to value” stories
Syllabus and teachers
Here are the main topics we will teach in this module through interactive lessons:
- Foundations and best practices of information theory and data communication applied to a data project.
- Understanding the different Data Visualization approaches: from fully-computational (like D3.js) to point-and-click platforms (such as Tableau or Microsoft BI).
- A light introduction to D3.js programming paradigm
- Deep dive into Vega Framework (Vega is aimed to describe the visual appearance and interactive behaviour of a visualization in a JSON format, and generate dynamic and interactive web-based views using Canvas or SVG)
- Prototyping effective data visualizations following the design process and best practices of data visualization theory
This session will also include:
- Lectures from our network of experts:
- Matteo Moretti, Sheldon Studio
- Giovanni Magni, Accurat
- Insights on the history and future of the open source libraries, how to contribute and participate in community events
- Hands-on sessions and group exercises to put in practice the lessons learnt
Resident teachers and coordinators:
Fabio Franchino
Founder and Computational Designer at TODO
Laura Pippinato
Designer at TOP-IX
Christian Racca
BIG DIVE Program Manager
Stefania Delprete
Data Scientist at TOP-IX
Are you interested in attending more than one BIG DIVE training module and becoming a Data Expert at 360°?
Look the other modules and leverage the discount package!
| From Zero to Data Science with Python (beginner class) – September 2020 |
| Machine and Deep Learning Intensive (advanced class) – October 2020 |
| Deep Dive into Data Engineering (advanced class) – December 2020 |
Application process
Here’s a timeline of what will happen:
| February 17 | Registrations opening |
| May 31 |
Early-bird expiring |
| November 8 |
Registration closing |
| From Nov 16 to Nov 20 |
BIG DIVE Communicating and Visualizing Data |
The application process starts with a self-evaluation of the prerequisites (mostly related to your programming skills and Maths background) needed to access and fully enjoy the course. Optional skills were taken into consideration to create a balanced classroom. You can download here a preview of the questions and requirements of the official application form.
In the form, you can tell us more about you, your previous experiences and why we should choose you. We strongly encourage you to make a short video to stand out among the other candidates!
After we receive the applications our team starts the screening. Candidates might be contacted by the organizers and asked to provide more information about skills or to attend an interview (in person or using a remote audio-video communication tool). The selection process continued till the official registration closure to create progressively a class of a minimum of 8 and maximum 20 Divers.
Applicants selected before the official end of registration were asked to pay a deposit (40% of the total due fee – according to the profile). In case of missing deposit (deadline is one week after the request) the candidate loses the priority in the selection queue. In case a selected candidate renounces to participate, a new Diver is selected. The deadline for asking for the deposit refund is fifteen days before the course begins (we do not refund unused portions of the training).
If you purchase more than one module, the deposit amount, payment deadlines and refunding options will be discussed and communicated privately.
All the news about selection, exclusion and deposit request are communicated by email through the email address inserted in the application form.
Logistics and technical information
From Monday to Friday from 9:30 am to 4:30 pm. Additional time was reserved for special lectures, exercises and “homework”.
One day of absence is allowed on a total of five training days.
Venue: Online via WebEx!
Technical prerequisites: a full list of technical prerequisites will be communicated in advance.
Training language: English.
Organizer and partners
BIG DIVE 2020 is organized by:
In collaboration with:
With the patronage of:
With the support of:
Check the frequently asked questions
A copy of your University ID card or any certificate proving you are a student at the time of application. You can send it at info.bigdive@top-ix.org after you filled up the form online.
The requirements for the “Communicating and Visualizing Data” course are:
- You must be familiar with the basics of HTML, CSS and spreadsheet software.
- Knowledge in Adobe package, or Open Source equivalent, is a nice-to-have.
- JavaScript language knowledge is considered a nice-to-have skill during the selection process.
- Participants have to be equipped with a personal laptop (Linux, Mac or Windows is ok). Software to be installed will be communicated before lessons start.
As BIG DIVE will be taught in English, proper conversation and writing skills are required.
We will be happy to see your project portfolio if you have it. Send it us after the application to info.bigdive@top-ix.org
You video is strongly suggested for selection purposes, the letters of recommendation are not mandatory.
We encourage you do add them to your application to get know you and your motivation better and better evaluate your profile.
Yes, at the end of this course you’ll receive a certificate of attendance if you take part at more than 85% of the lessons and activities.
As this year BIG DIVE 2020 is divided in four modules, you’ll receive one certificate for each module you would decide to attend.
Yes, you can download a courtesy application form in PDF on this link.
It includes the full list of question and requirements.
Yes, from this link you can download a PDF of BIG DIVE 2020’s pamphlet here.
It can be useful to be shown to different department in you organization.