Analytics-University
The video explores the popularity of Python compared to R in both industry and academia and emphasizes the importance of considering job market and career prospects when choosing which language to learn. Python has become increasingly popular for data science and engineering, while R is still relevant in academia and certain industries. Additionally, learning SQL is essential for maximizing job prospects in the data analysis industry. While proprietary options such as SAS have advantages such as better user support, Python's community and available resources continue to improve, and big banks are moving towards using Python more often over SAS. Python is also seen as a better choice for future-proofing skills, particularly in industries involving large datasets.
popularity between the two in industry and academia, it is important for beginners to consider the job market and career prospects when choosing which language to learn. While some individuals may have a personal preference for one language over the other, it is crucial to prioritize acquiring skills that will help secure a reliable income. In recent years, Python has become increasingly popular in data science and engineering, surpassing even the long-standing favorite C language. While R is still relevant in academia and certain industries, such as statistics and econometrics, it has seen a decrease in use over time. Furthermore, learning SQL is a necessity to maximize job prospects in the data analysis industry.
In this section, the speaker briefly discusses making comparisons between Python and SAS and highlights that while there are some advantages to proprietary software like SAS, one disadvantage is the documentation may not be as good as with Python, where there is no incentive to document it well. The speaker notes that user support is also better for proprietary options such as SAS, while user support for R and Python often requires searching the internet for answers, especially for beginners. However, the speaker also notes that communities around open-source programming languages like Python are improving, and more resources like YouTube videos and blogs are available now than 10 years ago. While SAS is still popular in many big corporations and banks, the speaker notes that big banks are now moving towards using Python more often, and new employees who know how to use Python are increasingly preferred over those who only know SAS.
In this section of the video, the speakers discuss the popularity of Python compared to R in industry and academia. They agree that Python is a better choice for those looking to future-proof their skills, particularly in industries like marketing and banking where large datasets are involved. While some companies still use SAS for credit risk models, Python is seen as easier to use for newer models like upgraded boosting. The speakers also touch on the rise of automated software like data robots in response to difficulties in running multiple models across multiple platforms. They invite viewers to share their views on the topic and any tools they use in the comments section.
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