This video includes: Purpose of Data Science, Role of Data Scientist, Skills required for Data Scientist, Job roles for Data Scientist, Applications of Data Science, Career in Data Science.

1. What is Data Science ?

2. Data Science
• Data Science is the branch of Artificial Intelligence or we can say it is the
future of Artificial Intelligence.
• Now a days every Industry require Data science is for improvement of
business and customer satisfaction.

3. Data Science
• Data Science is the study of various machine learning algorithm to find the
hidden patterns in the available data.
• Data science required skills in mathematics, statistics, business, computer and
Information technology and domain knowledge.
• The main purpose is to transfer the row data into valuable information.
• Data can be collect from various field such as web smartphone, customers,
bank etc.

4. Purpose of Data Science
• Data is available as small in size mostly structured, semi-structured and large
in size unstructured.
• There are many sources of data such as texts, videos, images etc.
• For all these consequences we have to go for advanced analytical tools and
algorithms to draw meaningful insights.

5. Purpose of Data Science
• Decision tree reduce the selection process for various websites and provide
feasible decision.

6. Role of Data Scientist
• Data scientist identify the questions to understand the business problem
• Gather data from various sources, public data
• Process the data and convert it into suitable format for analysis
• Visualizing data
• Feed the data into algorithm or a statistical model
• Prepare the results and insights by deploying models into applications

7. Role of Data Scientist
• To find solutions and draw conclusions that are important for an
organization’s growth and business development
• The team of Data scientist include :
• a business analyst who defines the problem
• a data engineer who prepares the data
• an IT architect who oversees the underlying processes and infrastructure
• an application developer who deploys the models of the analysis into applications
useful to clients

8. Skills required for Data Scientist
• Posses knowledge of python programming, R-language, SQL database, SAS,
and sometimes Java, Scala
• Mathematical expertise, statistical thinking, technical acumen, and Multi-
modal communication skills, curious mind, Creativity
• Machine learning algorithms such as Regression, Clustering, Decision
Tree, Support Vector Machines, Naive Bayes etc.

9. Job roles for Data Scientist
• Data Scientist
• Machine Learning Engineer
• Data Consultant
• Data Analyst

10. Applications of Data Science
• Healthcare, Gaming, Image Recognition, Recommendation Systems,
Logistics, and Fraud Detection

11. Applications of Data Science
• Data science is already helping the airline industry, it optimize plan routes and
decide whether to schedule direct or connecting flights, forecast for flight delays,
offer promotional offers to individual according to customers.
• Product recommendations draws insights out of customers browsing history,
purchase history.
• Data Science predict the data by forecasting, lets take weather forecasting as
example
• Data Science also aids in effective decision making, Self-driving car is best example
• Data science helps in fraud detection, lets take example of COVID-19 vaccination

12. Career in Data Science
• Over the last 10 years, the job vacancies for data science and its related roles
have grown significantly around the world.
• In US 11.5 million jobs will be available at the end of 2026, as per US bureau
of labor statistics.
• The average salary of a data scientist in the US is $100,560 per annum and
in India, it’s 698,412 Rupees per annum. It is the highest salary paying job of
21st century.

13. Conclusion
• Data Science is very essential for companies in the coming decade.
• By incorporating data science techniques into business most organizations &
companies can forecast future growth and analyze for upcoming threats.
• Now, it’s the right time to start career in data science.

14. Thank You