Coursera

Information Visualization: Advanced Techniques (Coursera)

Offered by New York University,
Information Visualization: Advanced Techniques (Coursera)

This course aims to introduce learners to advanced visualization techniques beyond the basic charts covered in Information Visualization: Fundamentals. These techniques are organized around data types to cover advance methods for: temporal and spatial data, networks and trees and textual data. In this module we also teach learners how to develop innovative techniques in D3.js.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

Learning Goals
Goal: Analyze the design space of visualization solutions for various kinds of data visualization problems. Learn what designs are available for a given problem and what are their respective advantages and disadvantages.

  • Temporal
  • Spatial
  • Spatio-Temporal
  • Networks
  • Trees
  • Text

The course expects you to have some basic knowledge of programming as well as some basic visualization skills (as those introduced in the first course of the specialization).
Course 4 of 4 in the Information Visualization Specialization.

Syllabus

WEEK 1: Visualizing Geographical Data
WEEK 2: Visualizing Network Data
WEEK 3: Visualizing Temporal Data
WEEK 4: Interaction and Multiple Views

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Data Science Ethics (Coursera) Coursera
University of Michigan

Data Science Ethics (Coursera)

Data Science

What are the ethical considerations regarding the privacy and control of consumer information and big data, especially in the aftermath of recent large-scale data breaches? This course provides a framework to analyze these concerns as you examine the ethical and privacy implications of collecting and managing big data. Explore the broader impact of the data science field on modern society and the principles of fairness, accountability and transparency as you gain a deeper understanding of the importance of a shared set of ethical values.

Sep 21st 2026
4 Weeks
History Ethics Data Analysis
Details
Fundamentals of Data Analysis in Excel (Coursera) Coursera
Corporate Finance Institute

Fundamentals of Data Analysis in Excel (Coursera)

Economics & Finance Statistics & Data Analysis

Excel is the most widely used analysis tool in the world and a great starting point for diving into data analysis. In this course, you’ll apply Excel’s native tools to structure your data into spreadsheets and tables. You’ll then analyze and produce insights from that data using pivot tables. Finally, you’ll visualize those insights by building a dashboard in Excel. You’ll apply these skills using modern functionality like dynamic array formulas, linked data types, and Ideas in Excel. You’ll work hands-on with real-world scenarios, using datasets pulled from financial statements and retail sales.

Sep 21st 2026
5-12 Weeks
Excel Data Analysis Microsoft Excel
Details
Experimentation for Improvement (Coursera) Coursera
McMaster University

Experimentation for Improvement (Coursera)

Statistics & Data Analysis Data Science

We are always using experiments to improve our lives, our community, and our work. Are you doing it efficiently? Or are you (incorrectly) changing one thing at a time and hoping for the best? In this course, you will learn how to plan efficient experiments - testing with many variables. Our goal is to find the best results using only a few experiments. A key part of the course is how to optimize a system.

Sep 14th 2026
5-12 Weeks
Statistics Data Science Regression Models
Details
Structural Equation Model and its Applications | 结构方程模型及其应用 (普通话) (Coursera) Coursera
The Chinese University of Hong Kong

Structural Equation Model and its Applications | 结构方程模型及其应用 (普通话) (Coursera)

Statistics & Data Analysis

在社会学、心理学、教育学、经济学、管理学、市场学等研究领域的数据分析中，结构方程建模是当前最前沿的统计方法中应用最广、研究最多的一个。它包含了方差分析、回归分析、路径分析和因子分析，弥补了传统回归分析和因子分析的不足，可以分析多因多果的联系、潜变量的关系，

Sep 14th 2026
5-12 Weeks
Data Analysis LISREL Regression Analysis
Details
Statistical Inference and Hypothesis Testing in Data Science Applications (Coursera) Coursera
University of Colorado Boulder

Statistical Inference and Hypothesis Testing in Data Science Applications (Coursera)

Statistics & Data Analysis Data Science

This course will focus on theory and implementation of hypothesis testing, especially as it relates to applications in data science. Students will learn to use hypothesis tests to make informed decisions from data. Special attention will be given to the general logic of hypothesis testing, error and error rates, power, simulation, and the correct computation and interpretation of p-values. Attention will also be given to the misuse of testing concepts, especially p-values, and the ethical implications of such misuse.

Sep 21st 2026
5-12 Weeks
Statistics Hypothesis Statistical Inference
Details
Interprofessional Healthcare Informatics (Coursera) Coursera
University of Minnesota

Interprofessional Healthcare Informatics (Coursera)

Statistics & Data Analysis Data Science

Interprofessional Healthcare Informatics is a graduate-level, hands-on interactive exploration of real informatics tools and techniques offered by the University of Minnesota and the University of Minnesota's National Center for Interprofessional Practice and Education. We will be incorporating technology-enabled educational innovations to bring the subject matter to life. Over the 10 modules, we will create a vital online learning community and a working healthcare informatics network.

Sep 14th 2026
5-12 Weeks
Healthcare Informatics Telehealth
Details
Avoiding AI Harm (Coursera) Coursera
Fred Hutchinson Cancer Center

Avoiding AI Harm (Coursera)

Computer Science

This course is designed for those in roles with decision making power, to help them understand major topics to consider for using and developing Artificial Intelligence (AI) responsibly, including popular Generative AI tools like ChatGPT and others. It covers real-world examples of situations where AI was used in variety of fields and situations in ways hat revealed ethical concerns. Strategies are suggested to avoid doing harm working with AI, including a framework for working responsibly with AI.

Sep 21st 2026
1 Week
Artificial Intelligence Ethics Data Science
Details
Bayesian Statistics: Mixture Models (Coursera) Coursera
University of California, Santa Cruz

Bayesian Statistics: Mixture Models (Coursera)

Statistics & Data Analysis

Bayesian Statistics: Mixture Models introduces you to an important class of statistical models. The course is organized in five modules, each of which contains lecture videos, short quizzes, background reading, discussion prompts, and one or more peer-reviewed assignments. Statistics is best learned by doing it, not just watching a video, so the course is structured to help you learn through application.

Sep 21st 2026
5-12 Weeks
Statistics Data Analysis Statistical Models
Details