Data Visualisation

Birla Institute Of Technology And Science–Pilani (BITS–Pilani) via Coursera

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Details

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Paid Certificate Available
Duration & workload

3 days 20 hours 46 minutes
Sessions

Self-Paced
Level

Intermediate
Subtitles

English

Found in

Overview

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This course aims to prepare you for acknowledging and valuing the significance of data visualisations and visual analytics. You will be introduced to practical Exploratory Data Analysis (EDA) techniques using plotting libraries and tools on any tabular dataset. You'll learn how to design visualisations and dashboards that reduce cognitive load, effectively leveraging short-term memory. Throughout the course, we will cover a wide variety of topics, including utilising the power of storytelling with visualisations and dashboards to ensure your message deeply connects with your audience. Additionally, you will learn to compare and determine the appropriate data visualisation libraries and platforms for visual analysis. These topics are designed to give you an overview of what’s to come in this degree program, equipping you with the skills and knowledge needed to excel in the field of data visualisation.

Syllabus

Course Introduction

In this module, the learners will be introduced to the course and its syllabus, setting the foundation for their learning journey. The course's introductory video will provide them with insights into the valuable skills and knowledge they can expect to gain throughout the duration of this course. Additionally, the syllabus reading will comprehensively outline essential course components, including course values, assessment criteria, grading system, schedule, details of live sessions, and a recommended reading list that will enhance the learner’s understanding of the course concepts. Moreover, this module offers the learners the opportunity to connect with fellow learners as they participate in a discussion prompt designed to facilitate introductions and exchanges within the course community.

Visual Data Analytics

This module is designed to equip participants with a thorough understanding of data analysis, the different types of data analysis, and the pivotal role of visual analytics in decision-making. It delves into the data analysis process, emphasizing how visual analytics enhances data interpretation and decision-making. Participants will gain insights into the key roles involved in data analytics, explore a variety of data visualization libraries, tools, and platforms, and learn how to leverage these resources effectively.

Practical Statistics with Python

Quantitative information is crucial for organizations to function efficiently. The focus on metrics, KPIs, Balanced Scorecards, and performance dashboards highlights the importance of numbers in today's business environment. To communicate the stories behind these numbers effectively, it is essential to understand basic statistics and the principles of conveying quantitative information clearly, which is also the focus of this module.This module is designed to provide learners with the foundational skills necessary to perform data analysis using Python. It covers the selection and setup of the appropriate Python environment and Integrated Development Environment (IDE) tailored for data analysis tasks. Participants will gain a solid understanding of Python syntax, fundamental programming concepts, and the essential libraries commonly used in data analysis. By the end of this module, participants will be equipped with the tools and knowledge to effectively analyze data using Python.

Visualisation Basics

In today's data-driven world, the ability to effectively present quantitative information is crucial for decision-making and communication. This module introduces learners to key methods and tools for creating impactful visualisations. Participants will explore various visualisation types and gain hands-on experience using popular online spreadsheets and visualisation platforms. The module also focuses on developing proficiency in conducting thorough Exploratory Data Analysis (EDA), enabling learners to uncover insights and patterns within datasets.

Visualisation Design - Table

This module introduces tables and graphs as essential tools for presenting quantitative information. It provides clear guidelines for selecting the appropriate method based on the specific purpose. Tables should be structured according to the nature of the information they convey. The module further breaks down different types of tables and offers practical rules for aligning the content with the most suitable table format. Once you've decided to use a table and selected the most appropriate type, the module emphasizes the importance of refining the design for clarity and quick comprehension. Its goal is to empower participants with the skills to effectively present data using well-designed tables on popular platforms like Tableau.

Visualisation Design - Graphs

Understanding how our eyes perceive and our brains process visual information is crucial for effective graphical communication. This module delves into the science of visual perception and its application in presenting quantitative data. By grasping these principles, you'll learn to distinguish what graphical designs work, what don’t, and why. We will explore various types of graphs suited to different quantitative relationships and pair them with visual components and techniques to enhance clarity and effectiveness. This knowledge will equip you with practical skills for addressing real-world challenges in quantitative information presentation.

Visualisation Design - Advanced types

In today's data-driven world, the ability to create compelling visualisations is crucial. This module will equip you with the skills needed to transform raw data into visually appealing and informative graphics. This module is designed to elevate your data visualisation skills, focusing on sophisticated techniques that will enable you to convey complex data insights effectively. Students will learn to create sophisticated visualisations such as geo-maps, tree maps etc. enhancing their ability to convey complex data insights effectively leveraging Tableau's advanced capabilities.

Visualisation Design - Best Practices

This module equips learners with the essential design principles and practices necessary for creating effective graph components. Through a combination of theoretical insights and practical applications, participants will gain an understanding of the best practices for designing clear and impactful graphs. The module also emphasises the development of skills in visualising and communicating statistical findings using Python's powerful data visualisation libraries, including Matplotlib and Seaborn. By the end of this module, learners will be proficient in crafting visually compelling and informative data visualisations that enhance the clarity and impact of their statistical analyses.

Developing Interactive Visual Data Experiences

This module is designed to provide learners with the skills to create, present, and share data insights effectively using interactive visualisation tools like Bokeh and Tableau Cloud. The module is divided into three lessons that cover the fundamentals of building visualisations, enhancing data interaction, and collaborating through data-sharing platforms. This module equips learners with the skills to create dynamic and interactive data visualisations and effectively communicate insights using cutting-edge tools.

Building Dashboard Apps

This module focuses on the principles of designing effective dashboards and creating interactive data visualisations and data applications using Plotly and Dash. Learners will explore the key components that make a dashboard effective, such as usability, clarity, and design principles. Through hands-on experience, they will learn to build interactive dashboards that provide actionable insights and data-driven storytelling. The module covers best practices for dashboard design, including layout optimisation, colour theory, data-ink ratio, and interactivity considerations. Using Python, learners will gain practical experience creating interactive visualisations and dashboards with Plotly and developing data applications with Dash. By the end of the module, learners will be able to critically evaluate dashboard designs and develop customised data solutions for various use cases.

Storytelling with Data

This module delves into the art of storytelling through data visualisations, providing learners with the tools and knowledge to transform raw data into compelling narratives. The module begins by uncovering the foundational principles behind effective storytelling, emphasising how context shapes the way stories are perceived and understood. Learners will explore the critical components of story and narrative structure, gaining insight into how to construct a coherent and impactful story. Through a combination of theoretical knowledge and practical application, participants will learn to develop and present stories that not only convey information but also engage and persuade their audience. The module will focus on the use of visualisations as a powerful tool to enhance narratives, teaching learners how to select and design visual elements that support and strengthen their storytelling. By the end of this module, learners will be equipped to create data-driven stories that resonate with their audience and achieve their communication goals.