Statistical Data Visualization with Seaborn From UST from Coursera

Welcome to this Guided Project on Statistical Data Visualization with Seaborn, From UST.

For more than 20 years, UST has worked side by side with the world’s best companies to make a real impact through transformation. Powered by technology, inspired by people and led by their purpose, they partner with clients from design to operation.

With this Guided Project from UST, you can quickly build in-demand job skills and expand your career opportunities in the Data Science field. Producing visualizations is an important first step in exploring and analyzing real-world data sets. As such, visualization is an indispensable method in any data scientist's toolbox as well as a powerful tool to identify problems in analyses and for illustrating results.

In this project, we will employ the statistical data visualization library, Seaborn, to discover and explore the relationships in the Breast Cancer Wisconsin (Diagnostic) data set.

Using the exploratory data analysis (EDA) results from the Breast Cancer Diagnosis – Exploratory Data Analysis Guided Project, you will practice dropping correlated features, implement feature selection and utilize several feature extraction methods including; feature selection with correlation, univariate feature selection, recursive feature elimination, principal component analysis (PCA) and tree based feature selection methods.

Lastly, we will build a boosted decision tree classifier with XGBoost to classify tumors as either malignant or benign. By the end of this Guided Project, you should feel more confident about working with data, creating visualizations for data analysis, and have practiced several methods which apply to a Data Scientist’s role.

Let's get started!

What's inside

Syllabus

Project: Statistical Data Visualization with Seaborn

Welcome to this project-based course on Statistical Data Visualization with Seaborn. Producing visualizations is an important first step in exploring and analyzing real-world data sets.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops visualizations for data analysis, which is core for Data Scientists

Examines Seaborn, which is used for visual exploration

Meant for those who have completed the Exploratory Data Analysis with Breast Cancer data Guided Project

Uses UST software, which may not be what is used in industry

Builds in-demand skills, which can make learners more competitive in the job market

Reviews summary

Engaging stat viz with seaborn

Learners say this is an engaging and well designed course for beginners and intermediate learners looking to learn more about data visualization with Seaborn. The guided projects are well received and learners appreciate that the completed notebook is included in the resources so they can concentrate on learning rather than typing. Although the explanations in the second part of the course are noted as a bit vague, learners largely enjoy the bite sized course design and hands on approach.

Good instructor.

"Thankyou Sir , for explaining in a very simple way it helps me alot!"

"Good instructor, nice bite sized course design and hands on approach."

Good projects.

"Good project based course"

"Great project, would have been better with a larger dataset in my opinion."

"Awesome guided project."

Vague explanations.

"With more explanation, this could have been better by miles."

"The course is really good but i feel it would be even more good if there was more explanation."

"The course was really nice however, I faced little issues while connecting to the rhyme desktop."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Statistical Data Visualization with Seaborn From UST with these activities:

Review Python Basics

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Refresh your understanding of basic Python programming concepts, such as data types, variables, and control flow.

Browse courses on Python Programming

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Review Python tutorials and documentation
Practice writing simple Python scripts

Review data visualization techniques

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Refresh your understanding of data visualization techniques, including how to create different types of visualizations, such as histograms, scatterplots, and bar charts.

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Review online tutorials on data visualization techniques using Seaborn
Practice creating visualizations using Seaborn with a small dataset

Creating Histograms and Distributions

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Practice creating histograms and visualizing the distribution of each feature to understand the data distribution and identify outliers.

Browse courses on Univariate Analysis

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Load the dataset and import Seaborn
Use Seaborn's distplot() function to generate histograms
Examine the histograms and identify any interesting patterns or outliers

18 other activities

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Mentor other students in your course

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Mentor other students in your course. This will help you solidify your understanding of the course material and improve your communication skills.

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Identify a student who is struggling with the course material
Offer to help the student by providing tutoring or study sessions

Seaborn Tutorial

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Familiarize yourself with the Seaborn library by following a tutorial to visualize data.

Browse courses on Seaborn

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Read the Seaborn documentation
Follow a Seaborn tutorial
Create a visualization using Seaborn

Explore data visualization techniques with tutorials

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Enhance your understanding of data visualization techniques by following guided tutorials, reinforcing key concepts and developing practical skills.

Browse courses on Data Visualization

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Identify reputable online tutorials or courses on data visualization with Seaborn.
Follow the tutorials and practice the techniques presented.
Apply the learned techniques to analyze and visualize your own datasets.

Interactive Data Visualization for the Web

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Gain a deeper understanding of interactive data visualization techniques and best practices for web applications.

View Interactive Data Visualization for the Web: An... on Amazon

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Read the book and take notes
Implement some of the techniques in your own projects
Discuss the book with others and share your insights

Practice visualizing data with Seaborn

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Practice visualizing data using Seaborn. This will help you solidify your understanding of how to create different types of visualizations and how to interpret the results.

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Use the Breast Cancer Wisconsin (Diagnostic) dataset to create a variety of visualizations using Seaborn
Interpret the visualizations to identify patterns and trends in the data

EDA Practice

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Reinforce your understanding of EDA by practicing on your own dataset.

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Choose a dataset
Perform EDA on the dataset
Create visualizations to explore the data

Practice feature selection techniques

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Practice feature selection techniques to gain proficiency in identifying and selecting the most relevant features for data analysis.

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Study different feature selection algorithms and their applications.
Experiment with various feature selection methods on real-world datasets.
Analyze the results of feature selection and evaluate model performance.
Implement feature selection techniques in your own data analysis projects.

Pairwise Scatterplots

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Create scatterplots of all pairwise relationships of the features to identify potential relationships between different features.

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Load the dataset
Use Seaborn's pairplot() function to generate the scatterplots
Examine the plots and identify any interesting patterns or relationships
Draw conclusions about the relationships between the features

Group Discussion on Feature Selection Methods

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Participate in group discussions to exchange knowledge and perspectives on different feature selection methods, their strengths, weaknesses, and applications.

Browse courses on Feature Selection

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Join a study group or online forum
Prepare by reading up on feature selection techniques
Participate in discussions and share your insights
Take notes and summarize key points

Feature Extraction Techniques

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Explore advanced feature extraction techniques, such as principal component analysis (PCA) and recursive feature elimination (RFE), to enhance the model's performance.

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Read articles and tutorials on feature extraction methods
Implement the techniques using Python libraries such as scikit-learn
Evaluate the impact of feature extraction on model performance

Create a tutorial on data visualization with Seaborn

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Create a tutorial on data visualization with Seaborn. This will help you solidify your understanding of the material and can serve as a valuable resource for other students.

Browse courses on Seaborn

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Choose a topic for your tutorial
Write the tutorial in a clear and concise style

Data Visualization Project

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Apply your skills to a real-world dataset and showcase your ability to analyze and visualize data.

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Choose a dataset
Perform EDA on the dataset
Create visualizations to explore the data
Write a report summarizing your findings

Data Visualization Workshop

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Attend a workshop led by an experienced data visualization expert to gain hands-on experience and insights into effective data visualization techniques.

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Register for a workshop that aligns with your goals
Attend the workshop and actively participate in exercises
Practice the techniques taught in the workshop
Apply the knowledge gained to your own projects

Build a data visualization dashboard

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Create a data visualization dashboard to effectively communicate insights from the Breast Cancer Wisconsin dataset and gain hands-on experience in visualizing complex data.

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Gather and explore the Breast Cancer Wisconsin dataset.
Design and develop a data visualization dashboard using Seaborn.
Include interactive elements and visualizations to enhance user engagement.
Present and share your dashboard with peers or stakeholders for feedback.

Blog Post on Statistical Data Visualization

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Write a comprehensive blog post that explains the principles and best practices of statistical data visualization using Seaborn, including code examples and real-world use cases.

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Research the topic and gather information
Outline the blog post and write a draft
Create visualizations using Seaborn
Include code snippets and explanations
Publish the blog post and promote it

Create a data visualization dashboard

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Create a data visualization dashboard that presents insights from the Breast Cancer Wisconsin (Diagnostic) dataset. This will help you demonstrate your skills in data visualization and your ability to communicate insights from data.

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Choose a set of visualizations that effectively communicate the key insights from the data
Create a dashboard using a tool such as Tableau or Power BI

Interactive Visualization Dashboard

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Develop an interactive dashboard that allows users to explore the Breast Cancer Wisconsin dataset in various ways, such as filtering, selecting features, and changing visualization types.

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Design the dashboard layout and functionality
Implement the dashboard using a library such as Plotly or Dash
Deploy the dashboard to a web hosting platform
Share the dashboard with others for feedback and insights

Participate in a data visualization competition

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Participate in a data visualization competition. This will challenge you to apply your skills in a real-world setting and will help you build your portfolio.

Browse courses on Data Visualization

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Find a data visualization competition that is relevant to your interests
Create a data visualization that meets the competition requirements

Career center

Learners who complete Statistical Data Visualization with Seaborn From UST will develop knowledge and skills that may be useful to these careers:

Data Visualization Specialist

A Data Visualization Specialist designs and develops data visualizations to communicate insights from data. This course on Statistical Data Visualization with Seaborn is directly relevant to this role, as it provides hands-on experience with a variety of data visualization techniques and tools.

See salaries and explore the career path for Data Visualization Specialist

Data Scientist

A Data Scientist is a professional who uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course on Statistical Data Visualization with Seaborn can be useful for Data Scientists as it provides hands-on experience with data visualization techniques and tools, which are essential for effectively communicating data-driven insights to stakeholders.

See salaries and explore the career path for Data Scientist

Data Analyst

A Data Analyst is responsible for collecting, cleaning, and analyzing data to identify trends and patterns. This course on Statistical Data Visualization with Seaborn can be particularly useful for Data Analysts as it provides a solid foundation in data visualization techniques, which are crucial for presenting data insights in a clear and compelling manner.

See salaries and explore the career path for Data Analyst

Machine Learning Engineer

A Machine Learning Engineer designs, develops, and deploys machine learning models to solve complex problems. This course on Statistical Data Visualization with Seaborn can be beneficial for Machine Learning Engineers as it helps them understand how to visualize and interpret data, which is essential for building effective machine learning models.

See salaries and explore the career path for Machine Learning Engineer

Business Intelligence Analyst

A Business Intelligence Analyst uses data to help businesses make better decisions. This course on Statistical Data Visualization with Seaborn can be helpful for Business Intelligence Analysts as it provides practical experience with data visualization techniques, which are essential for communicating data-driven insights to business stakeholders.

See salaries and explore the career path for Business Intelligence Analyst

Statistician

A Statistician collects, analyzes, interprets, and presents data. This course on Statistical Data Visualization with Seaborn can be beneficial for Statisticians as it provides hands-on experience with data visualization techniques, which are essential for effectively communicating statistical findings.

See salaries and explore the career path for Statistician

Data Engineer

A Data Engineer designs, builds, and maintains data pipelines and infrastructure. This course on Statistical Data Visualization with Seaborn may be useful for Data Engineers as it provides an understanding of data visualization techniques, which can be helpful for monitoring data quality and identifying potential issues in data pipelines.

See salaries and explore the career path for Data Engineer

Software Engineer

A Software Engineer designs, develops, and maintains software applications. This course on Statistical Data Visualization with Seaborn may be useful for Software Engineers who work on data-intensive applications, as it provides an understanding of data visualization techniques, which can be helpful for designing user interfaces and dashboards.

See salaries and explore the career path for Software Engineer

Quantitative Analyst

A Quantitative Analyst develops and implements mathematical and statistical models to analyze financial data. This course on Statistical Data Visualization with Seaborn may be useful for Quantitative Analysts as it provides an understanding of data visualization techniques, which can be helpful for presenting financial insights to stakeholders.

See salaries and explore the career path for Quantitative Analyst

Market Researcher

A Market Researcher collects and analyzes data to understand consumer behavior. This course on Statistical Data Visualization with Seaborn may be useful for Market Researchers as it provides an understanding of data visualization techniques, which can be helpful for presenting market research findings to stakeholders.

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Epidemiologist

An Epidemiologist investigates the causes and patterns of diseases in populations. This course on Statistical Data Visualization with Seaborn may be useful for Epidemiologists as it provides an understanding of data visualization techniques, which can be helpful for presenting epidemiological findings to public health officials and stakeholders.

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Biostatistician

A Biostatistician applies statistical methods to biological and medical data. This course on Statistical Data Visualization with Seaborn may be useful for Biostatisticians as it provides an understanding of data visualization techniques, which can be helpful for presenting statistical findings to medical researchers and practitioners.

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Actuary

An Actuary analyzes and manages financial risks. This course on Statistical Data Visualization with Seaborn may be useful for Actuaries as it provides an understanding of data visualization techniques, which can be helpful for presenting financial risk assessments to stakeholders.

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Financial Analyst

A Financial Analyst analyzes financial data to make investment recommendations. This course on Statistical Data Visualization with Seaborn may be useful for Financial Analysts as it provides an understanding of data visualization techniques, which can be helpful for presenting financial insights to clients and stakeholders.

See salaries and explore the career path for Financial Analyst

Operations Research Analyst

An Operations Research Analyst uses mathematical and statistical techniques to improve the efficiency of operations. This course on Statistical Data Visualization with Seaborn may be useful for Operations Research Analysts as it provides an understanding of data visualization techniques, which can be helpful for presenting operational insights to stakeholders.

See salaries and explore the career path for Operations Research Analyst