Data science is an interdisciplinary field that uses scientific methods, statistics, and systems to extract insights from data. It combines principles from computer engineering, mathematics, artificial intelligence, and statistics to analyze large amounts of data.

1. Data Science Fundamentals:
Write your First Python Code
in 60 minutes

2. Contents
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▰What is Data Science?
▰Why Data Science?
▰How Data Science is utilizing in
industries
▰Data Science career?
▰Salary Range?
▰How Data Science work?
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3. Artificial Intelligence
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Artificial intelligence (AI) refers to
the simulation of human
intelligence in machines that are
programmed to think like humans
and mimic their actions. The term
may also be applied to any
machine that exhibits traits
associated with a human mind
such as learning and problem-
solving.

4. Machine Learning
Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically
learn and improve from experience without being explicitly programmed. Machine learning focuses on the
development of computer programs that can access data and use it learn for themselves.

5. Data Lifecycle

6. Data Science
Revolution

7. What is Data Science?
▰Data science is an
inter-disciplinary field
that uses scientific
methods, processes,
algorithms and
systems to extract
knowledge and
insights from
structured and
unstructured data.

8. Application of Data Science

9. Data Science Goals and
Deliverables
Here is a shortlist of common data science deliverables:
▰Prediction (predict a value based on inputs)
▰Classification (e.g., spam or not spam)
▰Recommendations (e.g., Amazon and Netflix recommendations)
▰Pattern detection and grouping (e.g., classification without known classes)
▰Anomaly detection (e.g., fraud detection)
▰Recognition (image, text, audio, video, facial, …)
▰Actionable insights (via dashboards, reports, visualizations, …)
▰Automated processes and decision-making (e.g., credit card approval)
▰Optimization (e.g., risk management)
▰Forecasts (e.g., sales and revenue)

10. Data Science applications
contd..

11. Microsoft Speech
Recognition Control
Microsoft Search
Engine
Data Science applications
contd..

12. Recommender Systems
predicting
movie ratings

13. Fraud Detection
▰Data Science is getting better
and better at spotting
potential cases of fraud
across many different
fields. PayPal, for example, is
using machine learning to
fight money laundering. The
company has tools that
compare millions of
transactions and can
precisely distinguish between
legitimate and fraudulent
transactions between buyers
and sellers.

14. AI in weather

15. AI—A Game Changer for Climate
Change and the Environment
▰AI has helped farmers get 30 percent
higher groundnut yields per hectare
by providing information on preparing
the land, applying fertilizer and
choosing sowing dates. In Norway,
AI helped create a flexible and
autonomous electric grid, integrating
more renewable energy.
▰And AI has helped researchers
achieve 89 to 99 percent accuracy in
identifying tropical cyclones, weather
fronts and atmospheric rivers, the
latter of which can cause heavy
precipitation and are often hard for
humans to identify on their own. By
improving weather forecasts, these
types of programs can help keep
people safe.

16. Financial Trading
▰Many people are eager to
be able to predict what the
stock markets will do on
any given day — for
obvious reasons. But
machine learning
algorithms are getting
closer all the time. Many
prestigious trading firms
use proprietary systems to
predict and execute trades
at high speeds and high
volume.

17. Natural Language Processing
(NLP)
▰NLP is being used in all
sorts of exciting
applications across
disciplines. Machine
learning algorithms with
natural language can
stand in for customer
service agents and
more quickly route
customers to the
information they need.

18. Data scientist career
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19. Salary Range in USA
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20. Who can learn Data Science ….
Undergraduate Students / Graduate students
To get job quickly
Professionals
To improve their skills
Professional in their mid-career
Retain their career in new emerging field of data science as whole
industry Is moving with Data science else ready to face challenges

21. Data Science as a Career
▰If you are passionate about building a career
in the hot field of data science, leverage that
to drive business innovation then this course
is for you.
▰Data Science is not just a career choice, it is
a paradigm shift that is shaping the future
that we are moving into.

22. Comparison

23. Python features
▰Simple and easy to learn
▰Compatible with running on cross platforms
▰It is high level and interpreted language
▰Perform data manipulation, analysis and
visualisation
▰Powerful libraries for machine learning
applications