Examples of using Data science in English and their translations into Bengali
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Computer
Data Science domain is a combination of several fields including Computer Science- there are instances when specific programming languages are needed to get a job done.
Dealing with unstructured and structured data, Data Science is a field that comprises of everything that related to data cleansing, preparation, and analysis.
This shift in skills including programming and data science is something that Cisco ASA training partners should think about.
Introduction Data science is an emerging field in industry,
Data Science being one of the most sought after jobs,
Data Science operations cannot be scaled up directly,
Data Science is a vast field and to be a data scientist,
Data science courses focusing on the core skills needed for AI development- mathematics, computer science
Data science has many focus areas and you have to choose the one you are interested in.
A data scientist would definitely agree that even though data science is a fast-paced and a vast domain, it is exciting as well at the same time.
If you are not particular about any data science course in India, you can choose
social, mobile, data science, IoT- converging together creates unprecedented opportunities to innovate in an unprecedented way.
to write down all that perspective, context, and advice in a way that has no prerequisites- in terms of either social science or data science.
An important distinction that has to be made towards understanding the difference between this and ML is that data science is a generalist approach while ML is a specialist approach.
For example, the research of Joshua Blumenstock and colleagues was a mixture of traditional survey research with what some might call data science.
This takes the form of a 3-month learning program from TALL and is aimed at the experienced talent in the data science space.
For example, the research of Blumenstock and colleagues was a mixture of traditional survey research with what some might call data science.
More generally, social researchers will need to combine ideas from social science and data science in order to take advantage of the opportunities of the digital age;
This sounds like a massive job, but they solved it using a powerful trick that is common in data science but relatively rare in social science: supervised learning; see figure 2.5.
The intersection of social science and data science is sometimes called computational social science. Some consider this to be a technical field, but this will not