Data Visualization with Python

The short answer is no. Though learning Python is critical for developing a career in AI or data science, you will still need other skills if you wish to get a job in AI or data science.

To give you a little background, for example, there is a constant buzzing debate about whether R or Python is best in data science and AI. IBM believes both languages are important, for they each have their strengths and weaknesses. However interestingly, they also have their similarities. Where Python is considered a general-purpose programming language, R has grown directly from statistical analysis. The question that experienced data scientists and those who work in AI are asking, therefore, is not which is best for data science or AI, but when is it best to use each language.

We recommend you read this article written by IBM if you like to find out more: 'https: //www.ibm.com/cloud/blog/python-vs-r'

This is a hot subject for debate in the world of data science. IBM considers the topic very well in a page dedicated to the subject (see link below). From IBM's perspective, both languages are valuable for data science, and each brings its own strengths and weaknesses. Both languages are popular in data science because they each work well for many data science tasks. These can range from data manipulation to big data exploration. Their differences can be best understood, therefore, through consideration of how each one has come into existence. Python came into being around 1989 and is considered a general-purpose programming language. However, R has grown directly from statistical analysis, and is therefore extremely powerful but more complex to use.

For more information on this, we recommend you read this article written by IBM

Data Visualization with Python is a course that runs online. In order to be able to use the course materials, therefore, you will need access to the internet. When you enroll for this course, you will be able to access the course materials via the course link in your dashboard immediately.

Self-paced courses are not run to a set schedule of live sessions or webinars. As long as you work through the modules and complete the course before the end date, you can work as quickly or as slowly as you want; you can set your own pace.

Yes, Data Visualization with Python is a mentored course. 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.