This document provides an introduction to data science, including definitions of data science, its impact and importance. It discusses how data science affects organizations and provides competitive advantages. Examples of data science applications are given across various domains like banking, healthcare, transportation and more. The document also outlines the road to becoming a data scientist and what skills are required, such as learning to code, mathematics, machine learning techniques and software engineering. In summary, data science uses scientific methods to extract knowledge and insights from data, it benefits society in areas like healthcare, transportation and environment, and becoming a data scientist requires strong coding and analytical skills.

1. INTRODUCTION TO
DATASCIENCE

2. LEARNING OBJECTIVES
• Apprehend the field of Data Science impact and
importance in the society
• Reflect on its applications, importance and advantages

3. CONTENTS
Why should study Data Science?
• How Does Data Science Impact Organizations?
• Application and Competitive Advantage of Data Science in Organization
• Importance of Data Science to Society
• Road to Become a Data Scientist

4. WHY WE ARE TALKING ABOUT
DATA SCIENCE?
Source: https://bit.ly/31HBHuQ

5. WHAT IS DATA SCIENCE?
• “Data Science is a new term. But in the same sense as
Columbus was discovered NEW Continent 1000 years
ago.
”
- Hector Garcia-Molina
Professor in the Departments
of Computer Science and
Electrical Engineering of
Stanford University

6. WHAT IS DATA SCIENCE?
• a multi-disciplinary field
that uses scientific
methods, processes,
algorithms and systems to
extract knowledge and
insights from structured
and unstructured data.
Source: https://bit.ly/30dekJB

7. WHAT IS DATA SCIENCE?
• A "concept to unify statistics, data analysis, machine
learning and their related methods" in order to
"understand and analyze actual phenomena" with data.
• Employs techniques and
theories drawn from many
fields within the context of
mathematics, statistics,
computer science, and
information science.

8. WHAT IS DATA SCIENCE?

9. WHAT IS DATA SCIENCE?
Fourth Paradigm of Science
• Thousand of years
- Empirical
• Few hundred of years
- Theoretical
• Last fifty years
- Computational
- “Query the world”
• Last twenty years
- eScience (Data Science)
- “Download the world”

10. WHAT IS DATA SCIENCE?
Data Science and others
• Statistics
• Big Data Analytics
• Business Analytics
• Business Intelligence
• Data(base) Management
• Visualization
• Machine Learning
• Data Mining
• Artificial Intelligence
• Predictive Modelling

11. WHAT IS DATA SCIENCE?
Big Data Science T
asks
• Facebooks
• Amazon
• Google
• Linkedln
• Netflix
• Rozetka
• Microsoft

12. WHAT IS DATA SCIENCE?
Regular Data Science
• Data Analysis
• Modelling Statistics
• Engineering / Prototyping

13. What do people look for in a data scientist?

14. What do people look for in a data scientist?

15. Data Science Roles

16. Roles Required in Data Science Project

17. WHAT IS DATA SCIENCE?
How to become a data scientist?
• Data Scientists need to know how to “CODE”

18. WHAT IS DATA SCIENCE?
How to become a data scientist?
• Other languages, tools, platforms and visualization

19. Learning Data Science with Python - Libraries

20. WHAT IS DATASCIENCE?
Learning Data Science with Python - Libraries

21. Learning Data Science with Python - T
ools

22. WHAT IS DATA SCIENCE?
How to become a data scientist?
• Learn to code

23. WHAT IS DATASCIENCE?
Data Scientist need to comfortable with:

24. WHAT IS DATA SCIENCE?
to learning machine learning &
Data Scientist need
software engineering

25. WHAT IS DATASCIENCE?
Who are the Data Scientist?

26. Who are the Data Scientist?

27. Who are the Data Scientist?

28. WHAT IS DATA SCIENCE?
https://bit.ly/2P4eyl0

29. WHAT IS DATA SCIENCE?

30. WHAT IS DATA SCIENCE?

31. APPLICATION OF DATA SCIENCE

32. APPLICATIONS OF DATA SCIENCE
• Security

33. APPLICATIONS OF DATA SCIENCE
• Sports

34. APPLICATIONS OF DATA SCIENCE
• Banking and Finance

35. APPLICATIONS OF DATA SCIENCE
• Internet Search

36. APPLICATIONS OF DATA SCIENCE
• Digital Advertisements

37. APPLICATIONS OF DATA SCIENCE
• Recommender System

38. APPLICATIONS OF DATA SCIENCE
• Image Processing

39. APPLICATIONS OF DATA SCIENCE
• Speech Recognition

40. APPLICATIONS OF DATA SCIENCE
• Gaming

41. APPLICATIONS OF DATA SCIENCE
• Price Comparison Websites

42. APPLICATIONS OF DATA SCIENCE
• Airline Routing Planning

43. APPLICATIONS OF DATA SCIENCE
• Fraud and Risk Detection

44. APPLICATIONS OF DATA SCIENCE
• Delivery Logistics

45. APPLICATIONS OF DATA SCIENCE
• Internet of Things (IoT)

46. APPLICATIONS OF DATA SCIENCE
• Health Care

47. APPLICATIONS OF DATA SCIENCE
• Augmented Reality

48. APPLICATIONS OF DATA SCIENCE
• Self-Driving Cars

49. APPLICATIONS OF DATA SCIENCE
• Robots

50. IMPACT OF DATA SCIENCE ON SOCIETY

51. IMPACT OF DATA SCIENCE ON
SOCIETY
• Saving Energy

52. IMPACT OF DATA SCIENCE ON
SOCIETY
• Data-Driven Hospitals

53. IMPACT OF DATA SCIENCE ON
SOCIETY
• A Cleaner Environment

54. IMPACT OF DATA SCIENCE ON
SOCIETY
• V
olunteer with a socially-oriented data science
program/organization

55. IMPACT OF DATA SCIENCE ON
SOCIETY
• Contribute via competitions

56. IMPACT OF DATA SCIENCE ON
SOCIETY
• Consider solutions to real-world problems that you
encounter

57. IMPACT OF DATA SCIENCE ON
SOCIETY
• Be thoughtful in professional work

58. IMPORTANCE OF DATA SCIENCE

59. IMPORTANCE OF DATA SCIENCE
1. Data science
customers in
manner.
helps brands to understand their
a much enhanced and empowered
2. It allows brands to communicate their story in such
a engaging and powerful manner.
3. Big Data is a new field that is constantly growing
and evolving.

60. IMPORTANCE OF DATA SCIENCE
4. Its findings and results can be applied to almost
any sector like travel, healthcare and education
among others.
5. Data science is accessible to almost all sectors.

61. Road to become a Data Scientist

62. Thank You