Data Visualization with Python

This course comprises five purposely designed modules that take you on a carefully defined learning journey. If you are thinking about taking the course separately, it is worth noting that it is part of the IBM Applied Data Science with Python Certificate Program and you may want to consider enrolling for the whole program rather than just enrolling for one course at a time.

It is a self-paced course, which means it is not run to a fixed schedule with regard to completing modules or submitting assignments. To give you an idea of how long the course takes to complete, it is anticipated that if you work 2-3 hours per week, you will complete the course in 5 weeks. However, as long as the course is completed by the end of your enrollment, you can work at your own pace. And don’t worry, you’re not alone! You will be encouraged to stay connected with your learning community and mentors through the course discussion space.

The materials for each module are accessible from the start of the course and will remain available for the duration of your enrollment. Methods of learning and assessment will include discussion space, videos, reading material, review questions, hands-on labs, a final assignment and a final exam.

Once you have successfully completed the course, you will earn your IBM Certificate.

As part of our mentoring service you will have access to valuable guidance and support throughout the course. We provide a dedicated discussion space where you can ask questions, chat with your peers, and resolve issues. Depending on the payment plan you have chosen, you may also have access to live classes and webinars, which are an excellent opportunity to discuss problems with your mentor and ask questions. Mentoring services may vary package wise.

After completing this course, you will be able to:

• Create plots and visuals.
• Do basic plotting with Matplotlib.
• Generate different visualization tools using Matplotlib, such as line plots, area plots, histograms, bar charts, box plots, and pie charts.
• Use Seaborn to create attractive statistical graphics.
• Use Folium to create maps and visualize geospatial data.

• Individuals who want to visualize different types of data.
• Individuals who want to gather better insights about data.
• Individuals seeking to visualize data in basic, advanced and specialized forms of data visualization techniques.

We recommend that you have completed the following courses:

• Python 101
• Data Analysis with Python