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Exploratory vs Confirmatory data analysis using Python

This Guided Project, Exploratory and Confirmatory Data Analysis using python, is for those who want to learn about different methods of data analysis. In this 2-hour-long project-based course, you will understand and apply Exploratory Data Analysis, build different Data visualizations, apply different exploration techniques based on the data at hand and define and understand the concept of Confirmatory Data Analysis.

This project is unique because you will learn how and where to start your data exploration. You will also learn how to implement different data visualizations using python and when to use them. To be successful in this project, you will need to be experienced in python programming language and working with jupyter notebook environment.

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Syllabus

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Develops foundational concepts and skills necessary for identifying skills gaps and solving analytical problems using python

Teaches data visualization techniques using plotly, which are essential for presenting and understanding data insights

Provides hands-on experience through a project-based approach, allowing learners to apply concepts and techniques

Suitable for individuals with prior experience in python programming and Jupyter Notebook environment

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Reviews summary

Practical python data analysis guided project

According to learners, this course offers a highly practical, project-based introduction to Exploratory and Confirmatory Data Analysis using Python. Students commend its clear explanations and hands-on application of Pandas and Plotly. Its concise 2-hour format is ideal for a quick refresher or for those who prefer to learn by doing. However, a significant number of reviews highlight that it assumes strong existing proficiency in Python and Jupyter, making it challenging for absolute beginners who might find the pace too fast and depth insufficient. It's best suited for intermediate users.

Delivers core concepts effectively within a short duration.

"The 2-hour format is great for a quick refresher or initial dive. I found the practical exercises very useful."

"Very practical and to the point. A bit more theory would be nice but for 2 hours, it's impressive."

"The course is quite short, as advertised. It gives a high-level view of EDA and CDA."

Provides valuable hands-on application of data analysis.

"This guided project is excellent for getting hands-on experience with EDA and CDA in Python."

"Loved the practical, hands-on nature. It reinforced my Python skills and introduced me to Plotly for better visualizations."

"The project-based approach helped solidify my understanding of when to use exploratory vs. confirmatory methods."

Provides a good introduction but lacks deep dives.

"Could be more in-depth on certain statistical aspects of CDA."

"The course content was fine, but it felt a bit rushed, probably due to its short duration. ... don't expect deep dives."

"For others, it might leave them wanting more depth. The practical part is decent, but some explanations feel rushed."

Requires strong existing Python, Pandas, and Jupyter skills.

"It assumes you are comfortable with Python and Jupyter, so it's not for absolute beginners."

"I struggled with this project. It says 'experienced in python programming language', but I felt it moved too fast."

"If you're not strong in Python, you'll be lost. This isn't a beginner course despite the 'guided project' format."

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 Exploratory vs Confirmatory data analysis using Python with these activities:

Book Review: Python Data Science Handbook

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Reading this book will provide you with a comprehensive overview of the Python data science ecosystem and best practices for data analysis.

View Python Data Science Handbook: Essential Tools... on Amazon

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Read the book and take notes.
Discuss the book with classmates or colleagues.
Apply the concepts from the book to your own data analysis projects.

Tutorial: Exploratory Data Analysis Techniques

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By following this tutorial, you will learn various exploratory data analysis techniques that will help you understand your data better.

Browse courses on Exploratory Data Analysis

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Watch the tutorial videos.
Complete the practice exercises.
Apply the techniques to your own data analysis projects.

Tutorial: Pandas and Jupyter Notebook Environment

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Following this tutorial will give you a solid foundation in using Pandas and Jupyter Notebook, which are essential tools for data analysis in Python.

Browse courses on Pandas

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Watch the tutorial videos.
Complete the practice exercises.
Install Jupyter Notebook and Pandas on your computer.
Try out the examples in the tutorials.

Four other activities

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Workshop: Machine Learning for Beginners

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Attending this workshop will provide you with a solid foundation in the basics of machine learning, which is a useful skill for data analysts.

Browse courses on Supervised Learning

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Attend the workshop and listen to the lectures.
Complete the practice exercises.
Ask questions and get help from the instructor.

Practice Data Visualization with Plotly

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Completing these practice drills will improve your ability to effectively visualize data using Plotly, which is a valuable skill for data analysts.

Browse courses on Plotly

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Complete the practice exercises in the Plotly documentation.
Find a dataset and create several different types of visualizations.
Share your visualizations with others and get feedback.

Attend a Data Science Meetup

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Attending a data science meetup will allow you to connect with other professionals in the field and learn about new trends and technologies.

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Find a data science meetup in your area.
Attend the meetup and introduce yourself to others.
Join in on the discussions and ask questions.

Volunteer at a Data Science Organization

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Volunteering at a data science organization will give you practical experience and allow you to contribute to the community.

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Find a data science organization that you are interested in volunteering for.
Contact the organization and inquire about volunteer opportunities.
Attend volunteer orientation and training.
Complete your volunteer hours.

Career center

Learners who complete Exploratory vs Confirmatory data analysis using Python will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts use their programming skills to analyze data, develop and implement data-driven solutions, and draw meaningful conclusions from large amounts of data. This course can help budding Data Analysts build a foundation in data exploration and visualization techniques. Understanding exploratory and confirmatory data analysis can help Data Analysts uncover trends, identify patterns, and make more informed decisions.

See salaries and explore the career path for Data Analyst

Data Scientist

Data Scientists use their programming skills to analyze data, develop and implement data-driven solutions, and draw meaningful conclusions from large amounts of data. This course can help Data Scientists build a foundation in data exploration and visualization techniques. Understanding exploratory and confirmatory data analysis can help Data Scientists uncover trends, identify patterns, and make more informed decisions.

See salaries and explore the career path for Data Scientist

Statistician

Statisticians use their programming skills to analyze data, develop and implement data-driven solutions, and draw meaningful conclusions from large amounts of data. This course can help budding Statisticians build a foundation in data exploration and visualization techniques. Understanding exploratory and confirmatory data analysis can help Statisticians uncover trends, identify patterns, and make more informed decisions.

See salaries and explore the career path for Statistician

Business Analyst

Business Analysts use their programming skills to analyze data, develop and implement data-driven solutions, and draw meaningful conclusions from large amounts of data. This course can help budding Business Analysts build a foundation in data exploration and visualization techniques. Understanding exploratory and confirmatory data analysis can help Business Analysts uncover trends, identify patterns, and make more informed decisions.

See salaries and explore the career path for Business Analyst

Data Engineer

Data Engineers use their programming skills to analyze data, develop and implement data-driven solutions, and draw meaningful conclusions from large amounts of data. This course can help budding Data Engineers build a foundation in data exploration and visualization techniques. Understanding exploratory and confirmatory data analysis can help Data Engineers uncover trends, identify patterns, and make more informed decisions.

See salaries and explore the career path for Data Engineer

Machine Learning Engineer

Machine Learning Engineers use their programming skills to analyze data, develop and implement data-driven solutions, and draw meaningful conclusions from large amounts of data. This course can help budding Machine Learning Engineers build a foundation in data exploration and visualization techniques. Understanding exploratory and confirmatory data analysis can help Machine Learning Engineers uncover trends, identify patterns, and make more informed decisions.

See salaries and explore the career path for Machine Learning Engineer

Quantitative Analyst

Quantitative Analysts use their programming skills to analyze data, develop and implement data-driven solutions, and draw meaningful conclusions from large amounts of data. This course can help budding Quantitative Analysts build a foundation in data exploration and visualization techniques. Understanding exploratory and confirmatory data analysis can help Quantitative Analysts uncover trends, identify patterns, and make more informed decisions.

See salaries and explore the career path for Quantitative Analyst

Risk Analyst

Risk Analysts use their programming skills to analyze data, develop and implement data-driven solutions, and draw meaningful conclusions from large amounts of data. This course can help budding Risk Analysts build a foundation in data exploration and visualization techniques. Understanding exploratory and confirmatory data analysis can help Risk Analysts uncover trends, identify patterns, and make more informed decisions.

See salaries and explore the career path for Risk Analyst

Data Visualization Specialist

Data Visualization Specialists use their programming skills to analyze data, develop and implement data-driven solutions, and draw meaningful conclusions from large amounts of data. This course can help budding Data Visualization Specialists build a foundation in data exploration and visualization techniques. Understanding exploratory and confirmatory data analysis can help Data Visualization Specialists uncover trends, identify patterns, and make more informed decisions.

See salaries and explore the career path for Data Visualization Specialist

Data Science Manager

Data Science Managers use their programming skills to analyze data, develop and implement data-driven solutions, and draw meaningful conclusions from large amounts of data. This course can help budding Data Science Managers build a foundation in data exploration and visualization techniques. Understanding exploratory and confirmatory data analysis can help Data Science Managers uncover trends, identify patterns, and make more informed decisions.

See salaries and explore the career path for Data Science Manager

Data Architect

Data Architects use their programming skills to analyze data, develop and implement data-driven solutions, and draw meaningful conclusions from large amounts of data. This course can help budding Data Architects build a foundation in data exploration and visualization techniques. Understanding exploratory and confirmatory data analysis can help Data Architects uncover trends, identify patterns, and make more informed decisions.

See salaries and explore the career path for Data Architect

Software Engineer

Software Engineers use their programming skills to analyze data, develop and implement data-driven solutions, and draw meaningful conclusions from large amounts of data. This course can help aspiring Software Engineers build a foundation in data exploration and visualization techniques. Understanding exploratory and confirmatory data analysis can help Software Engineers uncover trends, identify patterns, and make more informed decisions.

See salaries and explore the career path for Software Engineer

Product Manager

Product Managers use their programming skills to analyze data, develop and implement data-driven solutions, and draw meaningful conclusions from large amounts of data. This course can help aspiring Product Managers build a foundation in data exploration and visualization techniques. Understanding exploratory and confirmatory data analysis can help Product Managers uncover trends, identify patterns, and make more informed decisions.

See salaries and explore the career path for Product Manager

Consultant

Consultants use their programming skills to analyze data, develop and implement data-driven solutions, and draw meaningful conclusions from large amounts of data. This course can help aspiring Consultants build a foundation in data exploration and visualization techniques. Understanding exploratory and confirmatory data analysis can help Consultants uncover trends, identify patterns, and make more informed decisions.

See salaries and explore the career path for Consultant

Financial Analyst

Financial Analysts use their programming skills to analyze data, develop and implement data-driven solutions, and draw meaningful conclusions from large amounts of data. This course can help budding Financial Analysts build a foundation in data exploration and visualization techniques. Understanding exploratory and confirmatory data analysis can help Financial Analysts uncover trends, identify patterns, and make more informed decisions.

See salaries and explore the career path for Financial Analyst

Reading list

We've selected 14 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Exploratory vs Confirmatory data analysis using Python.

Python Data Science Handbook

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Provides a comprehensive overview of exploratory data analysis techniques using Python. It covers topics such as data cleaning, data visualization, and statistical modeling.

Exploratory vs Confirmatory data analysis using Python

Here's a deal for you

What's inside

Syllabus

Traffic lights

Save this course

Reviews summary

Practical python data analysis guided project

Activities

Career center

Reading list

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