This document provides an introduction to data science. It discusses what data science is, its importance and career opportunities. Data science is an interdisciplinary field that uses algorithms and processes to examine large amounts of data to uncover patterns and insights. The rise of data science is creating many new job openings and it will impact many industries. Data science helps brands understand customers and communicate engagingly. It also discusses applications of data science in healthcare, transportation, sports, government and other industries. Various techniques used in data science are also mentioned.

1. An Introduction
to Data Science
By: Pavan Kalyan

2. Agenda
• Data Science and Importances
• Data Science process
• How AI and Data Science are related to each other?
• Various techniques which are helpful to become a data scientist.
• Pandas and its importance in Data Science

3. What is Data Science?
Data science is an
interdisciplinary field that uses
algorithms, procedures, and
processes to examine large
amounts of data in order to
uncover hidden patterns,
generate insights, and direct
decision making.

4. IMPORTANCES OF DATA SCIENCES
• Career oppurtunities:
*"The rise of Data Science needs will create roughly 11.5 million job openings
by 2026" US Bureau of Labour Statistics
*"By 2026, Data Scientists and Analysts will become the number one emerging
role in the world." World Economic Forum
*Data Science and Artificial Intelligence are amongst the hottest fields of the
21st century that will impactall segments of daily life by 2025, from transport
and logistics to healthcare and customer service.

6. Importance of Data Science
• Data science helps brands to understand their customers in a much
enhanced and empowered manner.
• It allows brands to communicate their story in such a engaging and
powerful manner.
• Its findings and results can be applied for almost all the sectors like
travel, health care, and education among others.
• Data science, which solves problems by connecting relevant data for
later use, aids these emerging technologies. Facebook's facial
recognition technology is an example because it collects vast data on
current users over time and uses the same techniques to identify new
users.

7. Applications of Data Science
• Healthcare: Data science can identify and predict disease, and personalize healthcare
recommendations.
• Transportation: Data science can optimize shipping routes in real-time.
• Sports: Data science can accurately evaluate athletes’ performance.
• Government: Data science can prevent tax evasion and predict incarceration rates.
• E-commerce: Data science can automate digital ad placement.
• Gaming: Data science can improve online gaming experiences.
• Social media: Data science can create algorithms to pinpoint compatible partners.
• Fintech: Data science can help create credit reports and financial profiles, run accelerated
underwriting and create predictive models based on historical payroll data.
• Internet Searching

8. Internet Searching Image:

9. Recommender System

10. Facts on Data Generation
• Every day 2.5 quintillion bytes has been created.
• Statistics show that every day 500 tera bytes of new data are entered
into the databases of social network platforming facebook.

19. Various techniques which are helpful to become a
data scientist.