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Data Science Online Education.
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siteadmin on 04/02/2025 05:57:00

data science education, data scientist, data science, data scientist,  courses
on data science,

A scientific investigator are the term for scientist, while data is nothing but
information.Scientific investigation of information that enables an optimum
decision making can be the role of the data scientist. Various Decision supports
system rely on the volume of data, more the merrier. A lawyer as a data
scientist, is more like a liable to work legal data analytics with domain
knowledge that goes very deep. Many mistakenly believe a data scientist is just
a synonym for a data analyst, but this is wide of the mark. Data science is a
somewhat new concept for the legal industry, but it’s an active and, indeed,
“hot” field within many other sectors of the economy. Virtually every
industry now collects more data about what they do and how they do it than ever
before.
"Its better not to leave it on the table, but collect analyse the right data"
A data analysis can differ a bit as compared with data science, while analysis
is a deep study of data with hypothetical reasoning based on data examined. on
the other hand a data scientist works with the analytics of the data, and with
some mathematics, algorithms in conjunction with AI and machine language. A deep
domain knowledge is mandatory for a lawyer, this enables them to established the
relations between the various key parameters explored and scrapped from the
unstructured legal text.
Data scientists can be summarised as follows
1. BIG DATA : Database bases are  growing  at a prolific  growth rate . The
negative side of these data available for research and analysis, is that, its
completely unstructured. As a legal data scientist, the legal data has to be
deeply examined. Structured valuable information to be generated from the
volumes of the legal data. This involves deep study of the legal data, lets say
case laws. A case law is again a legal data that comprises of the details of a
legal case and its conclusion.
2. INFORMATION SCRAPING : For a data scientist reading and extracting the
valuable information from the data. The extracted information is stored in an
structure or in database terms a normalised form of data is generated, source of
which is un-normalised. This data is the basic data that is used by law data
scientist and is processed and worked with various algorithms. As already
mentioned a deep domain knowledge is mandatory for extracting valuable
information from the case laws, a compressed normalised data.
3. NETWORK ANALYTICS : Establishing various relations with the extracted data is
more of data network analysis. The data can be weighted with a numeric value
that relates to its importance in the complete context of the legal data"case
law". Not just the weightage but these numeric weights added to the various
extracted date also helps in the graphical representation of the data. The
domain knowledge is very important in conjunction with the practical experience.
An absurd analytics can ruin the outcome.
4. PREDICTIVE ANALYSIS : This is nothing but, working with the analytics of the
extracted valuable information of volumnous  data . The predictive analysis is
mainly done based on various algorithms that are deployed in AI or the machine
language that leverages to anticipate the final conclusion. The algorithms work
on the analytics of the data.
6. FORECASTING: The data science that mainly works with the important data
points generated to predict the outcome or extrapolate. This is why at each of
the above mentioned stage the knowledge is very important.
What does an individual needs to be a data scientist.
A data analysis can differ a bit with data science, while analysis is a deep
study of data with hypothetical reasoning based on data.While, a data scientist
works with the analytics and with some mathematical code or algorithms
KEYWORD :