Welcome To Data Science
Training Program
By 3RI Technologies

YOU WILL LEARN
What is Data
Science?
What is the job of
Data Scientist?
Why to become a
Data Scientist?
Tools for Data
Science
The growing demand
for data science
Data science as a
team sport

What is Data Science?
Data science continues to evolve as one of the
most promising and in-demand career paths for
skilled professionals. Today, successful data
professionals understand that they must advance
past the traditional skills of analyzing large
amounts of data, data mining, and programming
skills. In order to uncover useful intelligence for
their organizations, data scientists must master
the full spectrum of the data science life cycle and
possess a level of flexibility and understanding to
maximize returns at each phase of the process.

These professionals are well-rounded, data-driven individuals with
high-level technical skills who are capable of building complex
quantitative algorithms to organize and synthesize large amounts of
information used to answer questions and drive strategy in their
organization. This is coupled with the experience in communication
and leadership needed to deliver tangible results to various
stakeholders across an organization or business. They possess a
strong quantitative background in statistics and linear algebra as well
as programming knowledge with focuses in data warehousing,
mining, and modeling to build and analyze algorithms.
What is the job of Data
Scientist?

Glassdoor ranked data scientist as the #1 Best Job in America in 2018 for
the third year in a row. 4 As increasing amounts of data become more
accessible, large tech companies are no longer the only ones in need of
data scientists. The growing demand for data science professionals
across industries, big and small, is being challenged by a shortage of
qualified candidates available to fill the open positions.The need for data
scientists shows no sign of slowing down in the coming years. LinkedIn
listed data scientist as one of the most promising jobs in 2017 and 2018,
along with multiple data-science-related skills as the most in-demand by
companies. The statistics listed below represent the significant and
growing demand for data scientists.
Why to become a Data
Scientist?

Data scientists use many types of tools, but
one of the most common is open source
notebooks, which are web applications for
writing and running code, visualizing data,
and seeing the results—all in the same
environment. Some of the most popular
notebooks include Jupyter, RStudio, and
Zepplin. Notebooks are very useful for
conducting analysis but have their
limitations when data scientists need to
work as a team. Data science platforms
emerged to solve this problem.
Tools for Data Science

IT is often not able to manage both the increasing number of data
sources and the exponential number of requests to explore data.
Unfortunately, IT typically becomes a bottleneck where people within
the organization can be left waiting days or even weeks to access the
data they need for analytics, which is not acceptable in a world where
faster time-to-insight separates an industry’s leaders from its stragglers.
The need for data science experts is skyrocketing, and there is a
shortage of qualifiedpeopleto meet the demand. Data Scientist has
ranked #1 onGlassdoor’s list of the best jobs in Americaevery year since
2016. TheHarvard Business Review called thedata scientist the sexiest
job of the 21stcentury.
The growing demand for
data science

Classic descriptive analytics: An example is business intelligence. The
anticipated product of BI is to get historical reports or dashboards that brilliantly
illustrate trends or performance.
Ad Hoc reporting: This involves performing interactive queries on a data set. For
example: how many, how often, and where did a certain kind of item sell? And
then when we answer those questions, we dig deeper and drill down, drill up,
slice, dice, cube, to really understand what exactly is causing a dip in sales.
Predictive analytics: Instead of waiting for things to happen and then acting
(like the two building blocks described above), data can be analyzed proactively.
Here’s a B2B example: you create finished goods that are based on all material
that you purchased for a supplier. If the quantity of a particular material falls
below a certain stock, an alert will trigger to notify the purchasing team to order
more, so the production line working on this good won’t have to stop and wait
for the material.
Building blocks of data
science

Data engineers and architects can prepare
and organize the data
Business analysts can apply business
strategy to the data
Developers can write code to leverage the
data science model and applying it into an
application
To be successful, data science requires
contributions from others in the enterprise, and
thus should be treated as a team sport:
Data science as a team
sport

3RI Technologies is a Leading
Online/classroom Training
Provider since 2010 for
Software Development Courses
in Pune. It is one of the best
Online / Classroom Training
Institute, which provides High-
Quality Industry Level Training
with Real Time Projects. 3RI
Technologies is ISO 9001:2015
certified company imparting IT
training from basic to advanced
technologies.
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