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Data science
- 1. What is DataScience ?
- 2. Data Science • DataScience 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 • DataScience 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 DataScience • 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 DataScience • Decision tree reduce the selection process for various websites and provide feasible decision.
- 6. Role of DataScientist • 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 DataScientist • 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 forData 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 forData Scientist • Data Scientist • Machine Learning Engineer • Data Consultant • Data Analyst
- 10. Applications of DataScience • Healthcare, Gaming, Image Recognition, Recommendation Systems, Logistics, and Fraud Detection
- 11. Applications of DataScience • 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 DataScience • 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 Scienceis 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.
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