YouTube Link : https://www.youtube.com/watch?v=jV5FGsc2zxk Intellipaat Data Science training: https://intellipaat.com/data-scientist-course-training/ Read complete Data Science tutorial here: https://intellipaat.com/blog/tutorial/data-science-tutorial/

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01
Who should become a
Data Scientist
04
02
Career paths in
Data Science
03
05
Skills looked in a
Data Scientist
Further Learning
How to land a
Data Science Job

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Who should become
a
Data Scientist

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Who should become a Data Scientist?
Any person with analytical thinking, likes to find patterns in data and are good with
visualizations can become data scientists

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Who should become a Data Scientist?

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Who should become a Data Scientist?
Let’s say, you are into pre-sales and want to get into a data science

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Who should become a Data Scientist?
Marketing?

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Who should become a Data Scientist?
Want to do visualization?

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Who should become a Data Scientist?
A career in Data Science will give you all these perks:
In Demand Job Abundance Highly Paid

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Who should become a Data Scientist?
Data visualization Machine Learning Deep Learning Pattern Recognition

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Career paths in Data Science

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Career paths in Data Science
1
BUSINESS
INTELLIGENCE ANALYST
2
DATA
ENGINEER
MACHINE LEARNING
ENGINEER
3 4
DATA
ANALYST
5
DATA
SCIENTIST

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Career paths in Data Science
1
BUSINESS
INTELLIGENCE ANALYST
BI analyst uses data to help figure out market and business trends to
get a picture of the company’s position
Average salary: $90,000

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Career paths in Data Science
They design, build, and maintain data architectures for large-scale
applications considering the types of data
Average salary: $115,000
2
DATA
ENGINEER

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MACHINE LEARNING
ENGINEER
3
Career paths in Data Science
ML engineers help create learning systems and algorithm which are
implemented in applications
Average salary: $130,000

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4
DATA
ANALYST
Career paths in Data Science
Data Analysts use tools to provide solutions to questions which
require deep understanding of data
Average salary: $70,000

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5
DATA
SCIENTIST
Career paths in Data Science
Data scientists use statistics and build algorithms to make predictions
about complex data systems. Final product would be great visuals.
Average salary: $120,000

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Skills looked in a
Data Scientist

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Skills looked in a Data Scientist
• Knowing statistical programming
language, like R or Python is a very
vital skill
• Also, a database querying language
like SQL is a good start
• Mathematical skills are a positive
Programming Skills Statistical Skills
• A good understanding of statistics is vital
• Being familiar with statistical tests,
distributions, maximum likelihood
estimators is a plus
• This will help for machine learning as well
Machine Learning
• Knowing k-nearest neighbors, random
forests, ensemble methods, and more
algorithms are a plus
• All of these can be implemented in
Python or R directly
• Knowledge of models are a major plus

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Skills looked in a Data Scientist
• To be a data scientist you’ll need a
solid understanding of the industry
you’re working in
• This will help in knowing what
business problems your company is
trying to solve
Business Acumen Data Visualization
• The business world produces a vast
amount of data frequently. This data
needs to be translated into a format that
will be easy to comprehend.
• As a data scientist, you must be able to
visualize data with the aid of data
visualization tools such as Matplottlib,
and Tableau
Data Wrangling
• Ability to process and work with messy
and difficult data
• Handling data with inconsistent
formatting, missing values etc..
• Very important skill for day-to-day as
well

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Skills looked in a Data Scientist

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How to land a
Data Science Job

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How to land a Data Science Job?
Some pointers which you can follow
1. Take up a data science internship; because experience is experience
2. Grow your connections on the web and real life
3. Involve in Git open source data science project
4. Make your resume talk about your passions
5. Do a certification training with real-time projects which can add
amazing value

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Learning Path:
Data Scientist

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Data Scientists’ Learning Path
Simplified:
Basic W’s of
Data Science
Basics of Mathematics
and Statistics
Machine Learning
Concepts
Deep Learning Concepts Database
Technologies
Data
Visualization

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Further Learning..

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Further Learning

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Further Learning