Data science involves extracting meaningful insights from various types of data, including text, images, and numbers. It offers multiple career paths such as data scientist, business intelligence analyst, and data engineer, and has applications in areas like finance, healthcare, and e-commerce. By analyzing large datasets, data science helps answer complex questions and improve decision-making in various industries.

1. Data Science
Version 1.0

2. What is data?
• We often use the term data to refer
to computer information
• This information is either
transmitted or stored
• Any kind of information may it be
in numbers or text, or pictures is
termed as Data

3. Nature of data
Data comes in different types.
Some of the common types of data
include:
• Text
• Image
• Video
• Numbers
• Spreadsheets
• Sound

4. What is data science?
Extracting meaningful
insights from data is
known as data science.
Data when investigated
and carefully analyzed,
provides insights which
enriches our daily lives

5. Careers in data science?
Learning data science offers multiple career options. Some of the common job
titles for data scientists include
• Data Scientist
• Business Intelligence Analyst
• Data Mining Engineer
• Data Architect
• Senior Data Scientist

6. Careers in data science?
Data Scientist
• Data Scientists are
data enthusiasts
who gather and
analyze large sets
of structured and
unstructured
data. They
analyze, process,
and model data
and later interpret
the results to
create actionable
plans for
companies and
organizations.
Business
Intelligence Analyst
• Business
Intelligence
Analysts use data
to assess the
market and find
the latest
business trends in
the industry. This
helps to develop a
clearer picture of
how a company
should shape its
strategy.
Data Engineer
• Data Engineer
examines not only
the Data for their
own business but
also that of third
parties. In
addition to mining
data, a data
engineer creates
robust algorithms
to help analyze
the data further.
Data Architect
• Data Architects
work closely with
users, system
designers, and
developers to
create a blueprint
that data
management
systems use to
centralize,
integrate and
maintain the data
sources.
Senior Data
Scientist
• Senior Data
Scientists
anticipate the
business's needs
in the future.
Although they
might not be
involved in
gathering data,
they play a high-
level role in
analyzing it.

7. How data science
helps us?
Simply stated, data science
helps us answer different types
of questions from data.

8. Pre-requisites for data collection
Quality of the
Data
Completeness
of data
Format of
data

9. Some applications of data science
Digital
Advertisements
Speech
Recognition

10. Real-world Applications of Data Science
1. In Search Engines
The most useful application of Data Science is Search Engines. As we know when we want to search for something
on the internet, we mostly use Search engines like Google, Yahoo, DuckDuckGo and Bing, etc. So Data Science is
used to get Searches faster.
2. In Transport
Data Science is also entered in real-time such as the Transport field like Driverless Cars. With the help of Driverless
Cars, it is easy to reduce the number of Accidents.
3. In Finance
Data Science plays a key role in Financial Industries. Financial Industries always have an issue of fraud and risk of
losses. Thus, Financial Industries needs to automate risk of loss analysis in order to carry out strategic decisions for
the company. Also, Financial Industries uses Data Science Analytics tools in order to predict the future. It allows the
companies to predict customer lifetime value and their stock market moves.

11. 4. In E-Commerce
E-Commerce Websites like Amazon, Flipkart, etc. uses data Science to make a better user experience with
personalized recommendations.
5. In Health Care
In the Healthcare Industry data science act as a boon. Data Science is used for:
Detecting Tumor.
Drug discoveries.
Medical Image Analysis.
Virtual Medical Bots.
Predictive Modeling for Diagnosis etc.

12. 6. Image Recognition
Currently, Data Science is also used in Image Recognition. For Example, When we upload our image with our
friend on Facebook, Facebook gives suggestions Tagging who is in the picture. This is done with the help of
machine learning and Data Science. When an Image is Recognized, the data analysis is done on one’s Facebook
friends and after analysis, if the faces which are present in the picture matched with someone else profile then
Facebook suggests us auto-tagging.