Data science is a field that focuses on analyzing large amounts of data using tools and techniques to discover patterns and make business decisions. Data scientists utilize machine learning algorithms to develop predictive models from multiple sources of data in different formats. Data has become a valuable asset like oil in the 21st century that can help organizations improve decision making. The career is expected to grow exponentially and data scientists can earn more than average IT workers.

1. CAREER IN DATA
SCIENCE

2. What is Data Science?
UNDERSTANDING DATA SCIENCE
Data Science is a form of science that focuses
on dealing with huge chunks of data by using
modern data analysis tools and techniques to
discover hidden patterns, meaningful insights,
and make critical business decisions.
A Data Science professional has to utilize
complicated machine learning algorithms to
develop predictive models. There could be
multiple sources present in different formats
used in data analysis.
DATA IS THE NEW OIL
Data is the new oil of the 21st century
because it is an untapped valuable asset. It
enables improved decision making, pattern
discovery, and predictive analysis.
It can help scientists to discover the main
reason for a problem by asking the right
questions. Data Scientists can perform an
exploratory study on huge sets of data. They
can also model the data by leveraging various
algorithms.
 The USA is at the forefront of the data science market
 By 2025, the Data Science industry is expected to grow exponentially, reaching $16 billion
 Data Scientists are expected to earn more than the average IT workforce
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3. Data
Empowers Business
Decisions
“Accuracy is always better than assumptions”
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4. Who is a Data
Scientist?
Data Scientists are the
masters of handling big data.

5. Job Roles and
Responsibilities
 Work with an organization to discover issues and
leverage data for effective decision making
 Develop algorithms and conduct experiments to supply
reports to the organization and customers
 Utilize statistical techniques and machine learning to
provide innovative solutions to problems
 Assess the genuineness of data sources and data-
gathering techniques
 Look for unexplored opportunities to use
datasets/insights/models
 Align with the organization’s data science strategy
 Help in developing relations with clients with the help
of data
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6. Data Analytics
Data scientists use their
technical and social science
skills to discover trends and
manage data as analytics
experts.
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7. What are the Steps
to Become a Data
Scientist?
Make up your Mind
A career in data science isn’t
going to be easy. You should
only pursue this field if you have
made up your mind to handle
the complicated challenges.
Consider a Specialization
You need to develop a
specialization in a particular
industry to expect better
earning opportunities.
Start Exploring the Required Skills
You have to become familiar with
the necessary skills to become a
data scientist. It includes a lot of
tools and techniques.
Enrol to the London School of
Emerging Technology
LSET provides the best project-
based and interactive data
science certification course to
learn data science.
Get an Entry-Level Job
Get your first job, consider a
company where will have a lot
of room for growth. You will
learn to work with a team.
Explore Additional Projects
Your quest to learn data science
should never end. Try to indulge
yourself in new projects after
working hours to learn more.
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8. The Technical Skillset Required to
Become a Data Scientist
1 3 5
6
4
2
Knowledge of
Database Statistics
Machine
Learning
Programming
Tools
Data Wrangling Data
Visualization
Big Data
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9. The Non Technical Skills Required to
Become a Data Scientist
1 3
2
Intellectual
Curiosity
Communication
Skills
Team Work
4
Business
Accumen
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10. Diverse Career
Options
Apart from being a Data Scientist, there
are numerous other career options in
data science that you can pursue.
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11. Data Analyst
This professional has to execute queries on the
database. She/he also modifies algorithms used for
reducing information from huge databases.
Languages:
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12. Data Architect
This professional has the responsibility to ensure
that data engineers have the most useful tools
and system to start working with data.
Languages:
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13. Data Engineer
This professional has the responsibility to update
the current systems with the improved version of
the latest technologies in order to improve the
overall efficiency of the databases.
Languages:
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14. Statistician
This professional has the responsibility to develop
the latest methodologies for engineers to work
with Languages:
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15. Database
Adminstrator
This professional has the responsibility to monitor,
operate, and maintain databases. S/he also works to
install, configure, define schemas, train users, and more.
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16. Data & Analytics
Manager
This professional has the responsibility of
improving the business process as a bridge
between business and IT
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17. Enrol to LSET’s Data Science
Certification Course
Project-Based
Learning
Flexible
Timings
Updated Curriculum
with the Latest
Technologies
Individual
Attention
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18. THANK YOU!
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London
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Phone: +44 (0) 20 3369 9909
Email: admission@lset.uk
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