"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.
Data Visualization with Python
Offert par
IBM
À propos de ce cours
591,595 consultations récentes
Résultats de carrière des étudiants
27%
ont commencé une nouvelle carrière après avoir terminé ce cours
35%
ont bénéficié d'un avantage concret dans leur carrières grâce à ce cours
11%
a obtenu une augmentation de salaire ou une promotion
Compétences que vous acquerrez
Python ProgrammingData VirtualizationData Visualization (DataViz)Matplotlib
Résultats de carrière des étudiants
27%
ont commencé une nouvelle carrière après avoir terminé ce cours
35%
ont bénéficié d'un avantage concret dans leur carrières grâce à ce cours
11%
a obtenu une augmentation de salaire ou une promotion
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Niveau intermédiaire
Approx. 11 heures pour terminer
Recommandé : 3 weeks of study, 4-5 hours/week
Anglais
Sous-titres : Anglais, Vietnamien
Programme du cours : ce que vous apprendrez dans ce cours
2 heures pour terminer
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 heures pour terminer
6 vidéos (Total 27 min), 1 lecture, 2 quiz
6 vidéos
Welcome4 min
Introduction to Data Visualization4 min
Introduction to Matplotlib6 min
Basic Plotting with Matplotlib4 min
Dataset on Immigration to Canada2 min
Line Plots3 min
1 lecture
Syllabus10 min
1 exercice pour s'entraîner
Introduction to Data Visualization Tools10 min
3 heures pour terminer
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 heures pour terminer
6 vidéos (Total 25 min)
6 vidéos
Area Plots4 min
Histograms4 min
Bar Charts3 min
Pie Charts4 min
Box Plots3 min
Scatter Plots4 min
2 exercices pour s'entraîner
Basic Visualization Tools10 min
Specialized Visualization Tools10 min
11 heures pour terminer
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.
11 heures pour terminer
6 vidéos (Total 15 min), 1 lecture, 5 quiz
6 vidéos
Waffle Charts1 min
Word Clouds1 min
Seaborn and Regression Plots2 min
Introduction to Folium2 min
Maps with Markers2 min
Choropleth Maps4 min
1 lecture
IBM Digital Badge2 min
2 exercices pour s'entraîner
Advanced Visualization Tools10 min
Visualizing Geospatial Data10 min
Avis
4.6
Meilleurs avis pour DATA VISUALIZATION WITH PYTHON
par DMMar 14, 2020
Good course, some of the lab assignments did not load properly so it was difficult to practice... (week 2 & 3). Assignment was good after using Jupyter Notebooks as the scripting interface. Thank you!
par SSNov 20, 2019
It's a really great course with proper hands on time and the assignments are great too. i got enough opportunity to explore the things which were taught in the course. Really Satisfied. Thanks :)
par MNMay 15, 2019
More in class projects similar to final assignment where we can challenge our knowledge as we are all remote and it takes time to communicate through the available coursera forums.\n\nThank you.
par RSJan 7, 2020
This course gives very well knowledge about different types of visualization techniques and helps to start with visualization. Coursera provided an amazing course with an amazing instructor.
par CKMar 12, 2020
Good coverage of different plots. Videos are somewhat repetitive regarding the dataset (most of them could be about 20% shorter due to this). Labs (in Jupyter Notebooks) are great practice.
par JKJul 6, 2019
Poorly put together course - especially the labs. Frequent misspellings, incorrect links and confusing instructions. The technical problems are a greater challenge than the course material.
par SBMar 5, 2020
The course was beautifully structured. I would like to request to add the conditions on which tiles Mapbox Bright works. At times the tiles dont work and we are not sure of the root cause.
par SSSep 24, 2019
Kindly update the final assessment of this course work since it is quite difficult to work with it, as the content related to the assessment cannot be found in the course videos. Thanks !
par MSJul 29, 2019
This module is extremely important for Data Scientist. This module gives you the confidence on how to explore, manage, display and visualize data concept to meet end-users requirements...
par FAOct 3, 2019
Good course, but I found the final assignment hard to complete, spent quiet sometime researching to be able to complete it. Providing the correct solutions would be helpful\n\nThanks
par FCFeb 28, 2020
The videos, the labs and working with real data make the course just great! Excellent resource for learning to visualize data using Matplotlib, Pandas, Seaborn and Folium. Thank you
par AMOct 7, 2018
The course had a great examples and samples for common and uncommon visualizations. The course lacked the background to be able to import the geojson properly for the final though.
par RLAug 7, 2018
Excellent tutorials, great labs and fun exercises - visualization is one of the most satisfying things about data science, and it is no surprise that this course is very enjoyable!
par CBOct 26, 2019
The final project was somewhat more challenging due to some file downloading issues. But I was able to get some help in the forums for that, which helped me accomplish my goals.
par DDMar 2, 2019
The best course in this specialization, so far. Great balance between theory and practice. Interesting and demanding exercises and assignment. Theory explained in friendly way.
par NVJul 30, 2019
The course contents and lab work are appropriate and useful, however the final lab assignment using folium 0.5 to generate a choropleth layer was fraught with technical errors.
par RCJan 14, 2019
Excellent course, especially the labs were very useful and served as a recap of what was learnt in the previous courses of this certification course. Very clear explanation.
par LDSep 28, 2019
Great Learning. A truly good course which is very apt to the title. Learning clearly on the data distribution plots like Scatter, Boxplots, Folium and Geopandas. Must Learn.
par PKJan 4, 2020
This course gives a solid knowledge on creating visualizations with Python. Please have in mind that you have a good familiarity with Pandas to take the most of this course.
par MLMar 24, 2020
Best of the 5 IBM Data Science Courses I've taken so far. Some problems connecting with the labs, but you can bypass these by downloading the ipynb's from cognitiveclass.ai.
À propos de IBM
IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame.
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