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Scott Rixner
and
Joe Warren
This if the final course in the specialization which builds upon the knowledge learned in Python Programming Essentials, Python Data Representations, and Python Data Analysis. We will learn how to install external packages for use within Python, acquire data from sources on the Web, and then we will clean, process, analyze, and visualize that data. This course will combine the skills learned throughout the specialization to enable you to write interesting, practical, and useful programs.
Read more
This if the final course in the specialization which builds upon the knowledge learned in Python Programming Essentials, Python Data Representations, and Python Data Analysis. We will learn how to install external packages for use within Python, acquire data from sources on the Web, and then we will clean, process, analyze, and visualize that data. This course will combine the skills learned throughout the specialization to enable you to write interesting, practical, and useful programs.
Read more
This if the final course in the specialization which builds upon the knowledge learned in Python Programming Essentials, Python Data Representations, and Python Data Analysis. We will learn how to install external packages for use within Python, acquire data from sources on the Web, and then we will clean, process, analyze, and visualize that data. This course will combine the skills learned throughout the specialization to enable you to write interesting, practical, and useful programs.
By the end of the course, you will be comfortable installing Python packages, analyzing existing data, and generating visualizations of that data. This course will complete your education as a scripter, enabling you to locate, install, and use Python packages written by others. You will be able to effectively utilize tools and packages that are widely available to amplify your effectiveness and write useful programs.
Register for this course and see more details by visiting:
OpenCourser.com/course/4jpyev/python
What's inside
Syllabus
Week 1
This module will discuss the importance of using and writing documentation. The Python documentation is a valuable resource for learning about language features you haven't seen yet.
Read more
Syllabus
Week 1
This module will discuss the importance of using and writing documentation. The Python documentation is a valuable resource for learning about language features you haven't seen yet.
Read more
Week 2
This module will teach you about packages and modules in Python, including how to install packages and how to create your own modules. You will also learn to use the Pygal plotting library.
Week 3
This module will teach you about Python sets. Sets are used to hold unordered collections of data without duplicates. We will also discuss efficiency.
Week 4
The final project of the specialization will enable you to demonstrate mastery of the concepts you have learned up to this point. You will also be able to understand and compare different approaches to reconciling two data sets.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Introduces key tools and techniques for data analysis using Python
Builds upon the knowledge learned in the previous courses of the specialization
Enables learners to analyze existing data and generate visualizations of that data
Teaches learners how to install Python packages and write interesting, practical, and useful programs
Provides a solid foundation for learners to write useful programs
May require learners to take other courses as prerequisites
Save this course
Save Python Data Visualization to your list so you can find it easily later:
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Reviews summary
Python data visualization
According to students, Python Data Visualization is a challenging but rewarding course that provides a solid foundation in Python programming and data visualization. Learners say that the course is well-structured and the instructors are knowledgeable and supportive. They also appreciate the hands-on projects and the engaged discussion forums. Overall, students highly recommend this course to those who want to learn more about Python and data visualization.
Students benefit from the support of a vibrant community of learners and mentors.
"If you have problems, you can go to the forum where you can turn to mentors."
"You are not alone."
The instructors are passionate and dedicated to helping students succeed.
"They've worked very hard to make students learn more and understand more."
"To improve study experience, they even developed a useful tool OwlTest, where you can find all your submissions (including your code and test results)."
Engaging and challenging projects help students build confidence in their abilities.
"The assignments for c3 and c4 are challenging, which helps build self-confidence."
"Although some problems are not easy, if you think more and try your best to debug, you'll make it!"
"In this course nothing is impossible as long as you do not give up."
Some assignments are unclear and frustrating to complete.
"The Project Assignments fails to create interest."
"Instead it gave a lot of confusion with challenging function naming and problem description."
"This course doesn't spoonfeed you much, while I learned a lot it felt largely like unguided failing and frantic googling."
The course focuses more on Python basics than on data visualization.
"The course is been titled for Data Visualization but the same is not reflected strongly in the contents."
"I was expecting more videos on pygal and matplotlib."
"Seems that I'm not sure i learned them or not."
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 Python Data Visualization with these
activities:
Review 'Python Crash Course' by Eric Matthes
Show steps
Complement your learning by reviewing a comprehensive book on Python programming.
View
Python Crash Course, 3rd Edition: A Hands-On,...
on Amazon
Show steps
-
Read the book
-
Take notes and highlight important concepts
-
Complete the practice exercises
Practice previous coding skills
Show steps
Refresh programming skills by revisiting prior learning.
Browse courses on
Python Programming
Show steps
-
Review previous course materials
-
Take practice coding tests
Follow Tutorials on Python Data Manipulation
Show steps
Expand your knowledge by following tutorials on Python data manipulation techniques.
Browse courses on
Data Cleaning
Show steps
-
Find tutorials on Python data manipulation
-
Work through the tutorials and practice the techniques
-
Apply the techniques to your own data
Four other activities
Expand to see all activities and additional details
Show all seven activities
Solve Python Coding Challenges
Show steps
Challenge your understanding by attempting to solve Python coding challenges.
Browse courses on
Python Programming
Show steps
-
Find online Python coding challenges
-
Attempt to solve the challenges
-
Review solutions and compare to your own
Participate in Python Coding Competitions
Show steps
Test your skills and learn from others by participating in Python coding competitions.
Browse courses on
Python Programming
Show steps
-
Find Python coding competitions
-
Register for the competition
-
Practice and prepare for the competition
Write a Python Script for Data Visualization
Show steps
Reinforce your understanding by creating a Python script that visualizes data using the Pygal library.
Browse courses on
Data Visualization
Show steps
-
Gather the data you want to visualize
-
Choose the appropriate Pygal chart type
-
Write the Python script to generate the visualization
Develop a Python Program for Data Analysis
Show steps
Demonstrate your proficiency by developing a Python program that performs data analysis on a dataset of your choice.
Show steps
-
Identify a dataset for analysis
-
Load the dataset into your Python program
-
Clean and process the data
-
Perform data analysis using Python libraries
-
Generate insights and conclusions from the analysis
Review 'Python Crash Course' by Eric Matthes
Show steps
Complement your learning by reviewing a comprehensive book on Python programming.
View
Python Crash Course, 3rd Edition: A Hands-On,...
on Amazon
Show steps
Show steps
Show steps
- Read the book
- Take notes and highlight important concepts
- Complete the practice exercises
Practice previous coding skills
Show steps
Refresh programming skills by revisiting prior learning.
Browse courses on
Python Programming
Show steps
Show steps
Show steps
- Review previous course materials
- Take practice coding tests
Follow Tutorials on Python Data Manipulation
Show steps
Expand your knowledge by following tutorials on Python data manipulation techniques.
Browse courses on
Data Cleaning
Show steps
Show steps
Show steps
- Find tutorials on Python data manipulation
- Work through the tutorials and practice the techniques
- Apply the techniques to your own data
Four other activities
Expand to see all activities and additional details
Show all seven activities
Solve Python Coding Challenges
Show steps
Challenge your understanding by attempting to solve Python coding challenges.
Browse courses on
Python Programming
Show steps
Show steps
Show steps
- Find online Python coding challenges
- Attempt to solve the challenges
- Review solutions and compare to your own
Participate in Python Coding Competitions
Show steps
Test your skills and learn from others by participating in Python coding competitions.
Browse courses on
Python Programming
Show steps
Show steps
Show steps
- Find Python coding competitions
- Register for the competition
- Practice and prepare for the competition
Write a Python Script for Data Visualization
Show steps
Reinforce your understanding by creating a Python script that visualizes data using the Pygal library.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Gather the data you want to visualize
- Choose the appropriate Pygal chart type
- Write the Python script to generate the visualization
Develop a Python Program for Data Analysis
Show steps
Demonstrate your proficiency by developing a Python program that performs data analysis on a dataset of your choice.
Show steps
Show steps
Show steps
- Identify a dataset for analysis
- Load the dataset into your Python program
- Clean and process the data
- Perform data analysis using Python libraries
- Generate insights and conclusions from the analysis
Career center
Learners who complete Python Data Visualization will develop knowledge and skills
that may be useful to these careers:
Data Visualization Engineer
Data Visualization Engineer
A Data Visualization Engineer uses Python to create visualizations that communicate data insights to stakeholders. Python Data Visualization can help you become a more effective Data Visualization Engineer by teaching you how to clean, process, analyze, and visualize data. The course also teaches you how to use Python packages to acquire data from sources on the Web, which is a valuable skill for Data Visualization Engineers.
Data Analyst
Data Analyst
A Data Analyst uses Python to extract and analyze insights from data. Python Data Visualization can help you become a more effective Data Analyst by teaching you how to clean, process, analyze, and visualize data. The course also teaches you how to use Python packages to acquire data from sources on the Web, which is a valuable skill for Data Analysts.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer uses Python to develop and implement machine learning models. Python Data Visualization can help you become a more effective Machine Learning Engineer by teaching you how to visualize data in a way that makes it easy to identify patterns and trends. The course also teaches you how to use Python packages to acquire data from sources on the Web, which is a valuable skill for Machine Learning Engineers.
Business Intelligence Analyst
Business Intelligence Analyst
A Business Intelligence Analyst uses Python to analyze data to identify trends and patterns that can help businesses make better decisions. Python Data Visualization can help you become a more effective Business Intelligence Analyst by teaching you how to visualize data in a way that makes it easy to identify patterns and trends. The course also teaches you how to use Python packages to acquire data from sources on the Web, which is a valuable skill for Business Intelligence Analysts.
Data Scientist
Data Scientist
A Data Scientist uses Python to build models to predict future events or outcomes. Python Data Visualization can help you become a more effective Data Scientist by teaching you how to visualize data in a way that makes it easy to identify patterns and trends. The course also teaches you how to use Python packages to acquire data from sources on the Web, which is a valuable skill for Data Scientists.
Statistician
Statistician
A Statistician uses Python to analyze data to draw conclusions about a population. Python Data Visualization can help you become a more effective Statistician by teaching you how to visualize data in a way that makes it easy to identify patterns and trends. The course also teaches you how to use Python packages to acquire data from sources on the Web, which is a valuable skill for Statisticians.
Market Research Analyst
Market Research Analyst
A Market Research Analyst uses Python to analyze data to understand consumer behavior. Python Data Visualization can help you become a more effective Market Research Analyst by teaching you how to visualize data in a way that makes it easy to identify patterns and trends. The course also teaches you how to use Python packages to acquire data from sources on the Web, which is a valuable skill for Market Research Analysts.
UX Designer
UX Designer
A UX Designer uses Python to analyze data to improve the user experience of digital products. Python Data Visualization can help you become a more effective UX Designer by teaching you how to visualize data in a way that makes it easy to identify patterns and trends. The course also teaches you how to use Python packages to acquire data from sources on the Web, which is a valuable skill for UX Designers.
Data Journalist
Data Journalist
A Data Journalist uses Python to analyze data to tell stories. Python Data Visualization can help you become a more effective Data Journalist by teaching you how to visualize data in a way that makes it easy to communicate insights to a general audience. The course also teaches you how to use Python packages to acquire data from sources on the Web, which is a valuable skill for Data Journalists.
Financial Analyst
Financial Analyst
A Financial Analyst uses Python to analyze financial data to make investment recommendations. Python Data Visualization can help you become a more effective Financial Analyst by teaching you how to visualize data in a way that makes it easy to identify patterns and trends. The course also teaches you how to use Python packages to acquire data from sources on the Web, which is a valuable skill for Financial Analysts.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst uses Python to analyze data to improve business operations. Python Data Visualization can help you become a more effective Operations Research Analyst by teaching you how to visualize data in a way that makes it easy to identify patterns and trends. The course also teaches you how to use Python packages to acquire data from sources on the Web, which is a valuable skill for Operations Research Analysts.
Software Engineer
Software Engineer
A Software Engineer uses Python to develop and implement software applications. Python Data Visualization can help you become a more effective Software Engineer by teaching you how to visualize data in a way that makes it easy to identify patterns and trends. The course also teaches you how to use Python packages to acquire data from sources on the Web, which is a valuable skill for Software Engineers.
Project Manager
Project Manager
A Project Manager uses Python to analyze data to track project progress and identify potential risks. Python Data Visualization can help you become a more effective Project Manager by teaching you how to visualize data in a way that makes it easy to identify patterns and trends. The course also teaches you how to use Python packages to acquire data from sources on the Web, which is a valuable skill for Project Managers.
Risk Analyst
Risk Analyst
A Risk Analyst uses Python to analyze data to identify and mitigate risks. Python Data Visualization can help you become a more effective Risk Analyst by teaching you how to visualize data in a way that makes it easy to identify patterns and trends. The course also teaches you how to use Python packages to acquire data from sources on the Web, which is a valuable skill for Risk Analysts.
Product Manager
Product Manager
A Product Manager uses Python to analyze data to make decisions about product development. Python Data Visualization can help you become a more effective Product Manager by teaching you how to visualize data in a way that makes it easy to identify patterns and trends. The course also teaches you how to use Python packages to acquire data from sources on the Web, which is a valuable skill for Product Managers.
For more career information including salaries, visit:
OpenCourser.com/course/4jpyev/python
Featured in The Course Notes
This course is mentioned in our blog,
The Course Notes. Read
one article that features
Python Data Visualization:
To read more articles from OpenCourser, visit:
OpenCourser.com/notes
Reading list
We've selected nine 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
Python Data Visualization.
Comprehensive guide to data science with Python. It covers all the essential topics, from data cleaning and wrangling to machine learning and deep learning. It great resource for anyone who wants to learn more about data science with Python.
Practical guide to data analysis with Python. It covers all the essential topics, from data cleaning and wrangling to data visualization and statistical modeling. It great resource for anyone who wants to learn more about data analysis with Python.
Comprehensive guide to machine learning with Python. It covers all the essential topics, from supervised learning to unsupervised learning to deep learning. It great resource for anyone who wants to learn more about machine learning with Python.
Comprehensive guide to deep learning with Python. It covers all the essential topics, from neural networks to convolutional neural networks to recurrent neural networks. It great resource for anyone who wants to learn more about deep learning with Python.
Comprehensive guide to data visualization with Python. It covers all the essential topics, from data cleaning and wrangling to data visualization to data storytelling. It great resource for anyone who wants to learn more about data visualization with Python.
Save
Is an introduction to computer science with Python. It covers all the essential topics, from basic programming concepts to data structures to algorithms. It great resource for anyone who wants to learn more about computer science with Python.
Beginner's guide to data science. It covers all the essential topics, from data cleaning and wrangling to data visualization to data modeling. It great resource for anyone who wants to learn more about data science.
Comprehensive guide to deep learning with Python, Keras, and TensorFlow 2. It covers all the essential topics, from neural networks to convolutional neural networks to recurrent neural networks. It great resource for anyone who wants to learn more about deep learning with Python, Keras, and TensorFlow 2.
Practical guide to data analysis and visualization with Python. It covers all the essential topics, from data cleaning and wrangling to data visualization to data storytelling. It great resource for anyone who wants to learn more about data analysis and visualization with Python.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/4jpyev/python
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Effort
This is a four week class with an expected workload of 5-7 hours per week.
Level
Introductory
Via
Coursera
Institution
Rice University
Instructors
Scott Rixner
Joe Warren
Language
English
Transcripts
Español
Français
Português
Deutsch
Italiano
中文
العربية
한국어
日本語
हिंदी
Nederlands
Svenska
Pусский
Türkçe
Polski
Ελληνικά
українська мова
magyar nyelv
Bahasa Indonesia
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اُردُو,
فارسی
বাংলা
tiếng Việt
پښتو
آذربایجان دیلی
This course belongs to a
collection
called
Introduction to Scripting in Python. It's comprised of four courses:
- Python Programming Essentials
- Python Data Visualization (viewing)
- Python Data Representations
- Python Data Analysis
Good to know
Introduces key tools and techniques for data analysis using Python
Builds upon the knowledge learned in the previous courses of the specialization
Enables learners to analyze existing data and generate visualizations of that data
Teaches learners how to install Python packages and write interesting, practical, and useful programs
Provides a solid foundation for learners to write useful programs
May require learners to take other courses as prerequisites
Featured in The Course Notes
Read
one article that features
this course,
Python Data Visualization
from our blog, The Course Notes:
To read more articles from OpenCourser, visit:
OpenCourser.com/notes
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