The world of data science has evolved at a dramatic pace in the last 12 months, owing to the growing demand in the IT and SaaS development industries for talented data scientists and analysts.
In this article, we have underlined the various nuances of the data science industry and what kind of certification in data science. In all these, Python skills get a massive preference from the hiring managers and Project leaders.
These roles are:
Data Science Generalist
Business managers are looking for productivity and efficiency in their projects of data science with Python. A generalist with certified Python experience and data management skills is preferred over a data science specialist.
Data Science Generalists are “the jack of all trades” in the current context of various data management projects. More and more companies are hiring generalists empowered with Python knowledge — these generalists have the ability to handle a wide range of data management operations across their business domain. In comparison to the specialists, generalists are able to contribute more to various types of data management tasks, including mining, analysis, and applications in IoT, 5G, Cloud Computing, Edge, and so on.
Deep Learning research is another top specialization in the Python domain. It is often clubbed with the experience in AI ML and Computer Automation techniques, which is not the best way to approach the trend in the data science field. Deep learning is a subset within machine learning applications that extensively deals with the field of ‘Unstructured Data management’. If you are looking to crack the Big Data game using AI ML techniques, pick Deep Learning specialization.
Natural Language Processing
NLP is the top platform foundation for any modern mobile app or software. Companies are investing heavily into NLP tools to upgrade their text to speech and voice technologies that would simplify the way they do Sales, Marketing, and Customer service. If you are enrolling in a data science with Python course, for statistical analysis, text representation, and machine learning techniques would become quintessential to your success.
Data engineering is a growing specialization for Cloud businesses.
In the past year, 93 percent of the world’s top 500 companies made strategic investments in the fields of data science to modernize their IT infrastructure and Cloud migrations. To manage the massive movement of data, companies hired at least 2 data analysts and one data scientist / or Chief Data Officer to implement strategically key data management policies.
Python has emerged as the focal point of all data science projects in the last year or so. Companies are organizing boot camps and workshops in Python to kick start their data engineering skills development programs.