"A picture is worth a thousand words". We are all familiar with this expression. It especially applies when trying to explain the insight obtained from the analysis of increasingly large datasets. Data visualization plays an essential role in the representation of both small and large-scale data.
Offered By
IBMAbout this Course
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Intermediate Level
Approx. 17 hours to complete
English
Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, Korean, German, Russian, English, Spanish, Persian
What you will learn
Describe the importance of data visualization.
Relate the history of Matplotlib and its architecture.
Apply Matplotlib to create plots using Jupyter notebooks.
Discover how to read CSV files into a Pandas DataFrame; process and manipulate the data in the DataFrame; and generate line plots using Matplotlib.
Skills you will gain
- Python Programming
- Data Virtualization
- Plotly
- Matplotlib
- Data Visualization (DataViz)
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Intermediate Level
Approx. 17 hours to complete
English
Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, Korean, German, Russian, English, Spanish, Persian
Offered by
IBM
IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.
Syllabus - What you will learn from this course
2 hours to complete
Introduction to Data Visualization Tools
In this module, you will learn about data visualization and some of the best practices to keep in mind when creating plots and visuals. You will also learn about the history and the architecture of Matplotlib and learn about basic plotting with Matplotlib. In addition, you will learn about the dataset on immigration to Canada, which will be used extensively throughout the course. Finally, you will briefly learn how to read csv files into a pandas dataframe and process and manipulate the data in the dataframe, and how to generate line plots using Matplotlib.
2 hours to complete
6 videos (Total 27 min), 2 readings, 2 quizzes
3 hours to complete
Basic and Specialized Visualization Tools
In this module, you learn about area plots and how to create them with Matplotlib, histograms and how to create them with Matplotlib, bar charts, and how to create them with Matplotlib, pie charts, and how to create them with Matplotlib, box plots and how to create them with Matplotlib, and scatter plots and bubble plots and how to create them with Matplotlib.
3 hours to complete
6 videos (Total 26 min), 2 readings, 4 quizzes
3 hours to complete
Advanced Visualizations and Geospatial Data
In this module, you will learn about advanced visualization tools such as waffle charts and word clouds and how to create them. You will also learn about seaborn, which is another visualization library, and how to use it to generate attractive regression plots. In addition, you will learn about Folium, which is another visualization library, designed especially for visualizing geospatial data. Finally, you will learn how to use Folium to create maps of different regions of the world and how to superimpose markers on top of a map, and how to create choropleth maps.
3 hours to complete
6 videos (Total 15 min), 2 readings, 4 quizzes
6 hours to complete
Creating Dashboards with Plotly and Dash
In this module you will get started with dashboard creation using the Plotly library. You will create a dashboard with a theme `US Domestic Airline Flights Performance`. You will do this using a US airline reporting carrier on-time performance dataset, Plotly, and Dash concepts learned throughout the course. Hands-on labs will follow each concept to make you comfortable with using the library. Reading lists will reference additional resources to learn more about the concepts covered.
6 hours to complete
4 videos (Total 17 min), 6 readings, 6 quizzes
Reviews
- 5 stars68.92%
- 4 stars19.83%
- 3 stars6.05%
- 2 stars2.76%
- 1 star2.42%
TOP REVIEWS FROM DATA VISUALIZATION WITH PYTHON
by AZApr 20, 2020
A great course for you to further understand the mechanics of data visualisation as well as providing a space for you to familiarise and test your understanding on the subject matter.
by JGApr 16, 2020
This is a very helpful course. It introduces a variety of data visualization tools. The interesting practices in the lab sessions inspired me to explore different solutions for a problem.
by HYMay 23, 2020
Excellent course. The labs really challenge you because some of the material is not directly taught or the syntax differs slightly from what is taught so you have to hunt for answers.
by AMAug 13, 2020
Great course, one of the best course to get hands-on learning for Data Visualization with Python. Particularly the lap exercise, it will make you think on every line of code you write. Excellent!!!
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