Data Visualization: Tools & Techniques

UC Berkeley Extension

What are the topics?

UC Berkeley Extension

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Who should attend

The Data Visualization course is ideal for professionals or students seeking to gain an understanding of data visualization, especially in the context of presenting data to make a compelling proposition. The course also teaches hands-on skills using Python, R, Power BI and D3.js.

About the course

As big data advances into every industry and organization, finding ways to effectively share and communicate data with diverse audiences remains challenging. Data visualization provides decision makers with a visual representation of their analytics that makes data easier to understand, parse, and act upon. Taught via live online sessions, this course is ideal for professionals or students who want to learn how to characterize the data required to create effective visualizations—and build practical skills using visualization tools that bring their data to life.

Emeritus and UC Berkeley Extension

UC Berkeley Extension is collaborating with online education provider Emeritus to offer a portfolio of high-impact online courses. These courses leverage UC Berkeley’s thought leadership in technical practice developed over years of research, teaching, and practice. By collaborating with Emeritus, we are able to broaden access beyond our on-campus offerings in a collaborative and engaging format that stays true to the quality of UC Berkeley. Emeritus’ approach to learning is formulated on a cohort-based design to maximize peer-to-peer sharing and includes live teaching with world-class faculty and hands-on project-based learning. In the last year, more than 30,000 students from over 120 countries have benefited professionally from Emeritus.

SYLLABUS

Module 1: Introduction to Visualization

  • Defining data visualization and why it’s important
  • The value and goals of visualization
  • Types of visualizations
  • Pragmatic and artistic visualization
  • Visual principles

Module 2: Data Management and Visualization

  • What is data management? Why is it important to visualization?
  • Classes of data services in the industry
  • Introduction to MySQL and SQL
  • Demonstration of connectivity from Python and Power BI

Module 3: Data Management and Visualization With Python

  • How to use Python for data visualization
  • Introduction to and comparison of Python for data visualization
  • Using Python libraries and techniques
  • Data management in Python and connecting to MySQL
  • Demos of visualizations in Python

Module 4: Data Management and Visualization With R

  • Using R for data visualization
  • Introduction to R for data visualization
  • Using R libraries and techniques
  • Data frames in R and connecting to MySQL
  • Demos of visualizations in R
  • Practical selection of which environment to use

Module 5: Custom (JavaScript) Visualizations

  • Overview and reasons to do custom visualizations
  • What it takes to create an application in these environments
  • Introduction to D3.js
  • Examples of D3.js

Module 6: Visualization Tools

  • Power BI
  • Power BI examples
  • Out-of-the-box software tools for data visualization

Module 7: Streaming Visualizations

  • Real-time data visualizations connected to devices/IoT
  • Introduction to streaming data
  • Using PowerBI to connect to streaming data
  • Solving problems with visualizations tools: IoT applications

Module 8: Bringing It All Together

  • Understanding the business problem
  • Gathering the data
  • Processing the data
  • Visualizing the data
  • Presenting the visuals
  • Additional solutions using favorite tools chosen by participants

ASSIGNMENTS

Intro to Data Visualization

  • Participants find visualizations and critique based on sound design principles

Intro to Data Management

  • Insights to data storage and data querying
  • Use data management principles to access data in MySQL
  • Leverage your knowledge to understand the data model of the data you’ll be accessing for visualization, and write a query in SQL to extract data in preparation for visualization

Data Visualization Using Python

  • Use Python to prepare and shape data using Pandas
  • Connect to popular relational databases (MySQL) with Python
  • Use that data to create visualizations
  • Pull data from the web into Python for visualization

Data Visualization Using R

  • Use R to prepare and shape data
  • Connect to popular relational databases (MySQL) with R
  • Use that data to create visualizations
  • Pull data from the web into R for visualization

LEARNING EXPERIENCE

Emeritus follows a unique online model. This model has ensured that nearly 90 percent of our learners complete their course.

Orientation Week

The first week is orientation week. During this week you will be introduced to the other participants in the class from across the world. You will also learn how to use the learning platform and other learning tools provided.

Weekly Goals

On other weeks, you have learning goals set for the week. The goals would include watching the video lectures and completing the assignments. All assignments have weekly deadlines.
 Recorded Video Lectures

The recorded video lectures are by faculty from the collaborating university.

Live Webinars

Every few weeks, there are live webinars conducted by Emeritus course leaders. Course leaders are highly-experienced industry practitioners who contextualize the video lectures and assist with questions you may have regarding your assignments. Live webinars are usually conducted between 1 pm and 3 pm UTC on Tuesdays and Wednesdays.

Clarifying Doubts

In addition to the live webinars, for some courses, the course leaders conduct Office Hours, which are webinar sessions that are open to all learners. During Office Hours, learners ask questions and course leaders respond. These are usually conducted every alternate week to help participants clarify their doubts pertaining to the content.

Follow-Up

The Emeritus Program Support team members will follow up and assist over email and via phone calls with learners who are unable to submit their assignments on time.

Continued Course Access

You will continue to have access to the course videos and learning material for up to 12 months from the course start date.   Assignments/Application Projects

Assignments are given out weekly and they are based on the lectures or tutorials provided. They need to be completed and submitted as per the deadline for grading purposes. Extensions may be provided based on a request sent to the support team.

Discussion Boards

It is an open forum where participants pin their opinions or thoughts regarding the topic under discussion.

  Emeritus Program Support Team

  • If at any point in the course you need tech, content or academic support, you can email program support and you will typically receive a response within 24 working hours or less.   Device Support

  • You can access Emeritus courses on tablets, phones and laptops. You will require a high-speed internet connection.   Emeritus Network

  • On completing the course you join a global community of 5000+ learners on the Emeritus Network. The Network allows you to connect with Emeritus past participants across the world.

Experts

Carmen Taglienti

Carmen has over twenty-five years’ experience as a Big Data Analytics and Data Management expert. He is a recognized leader in the Analytics, Data Visualization, Data Science, Data Governance and “Big Data” space. Currently Carmen leads up Global Data Management and Governance team for State Stre...

Videos and materials

Data Visualization: Tools & Techniques at UC Berkeley Extension

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Disclaimer

Coursalytics is an independent platform to find, compare, and book executive courses. Coursalytics is not endorsed by, sponsored by, or otherwise affiliated with any business school or university.

Full disclaimer.

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