This document discusses data science and the role of data scientists. It explains that data scientists collect and analyze raw data to generate meaningful insights that help with decision making. They understand phenomena and help organizations make decisions. The document also outlines the steps to learn data science, including learning programming languages like Python and R, statistics, data visualization with libraries like Matplotlib and Seaborn, machine learning algorithms, and completing projects.

1. DATA SCINCE
Individual Presentation
M. Hadeed
BSF2103180

2. What is data science….
• Collect the data analysis the data and generate report….
• Convert raw data into meaning full insights…. That helps to decision making
easily…
• PARTS:
• Collect
• Analyze
• Insights

3. DATA SCIETIST
• Understand and Explain the phenomena around them and help organization
to make decision
• Is a person who convert the raw data in to meaning full form that help the
man to take decision
• Now the coming days data scientist have a great career
• It’s the most popular skill job in the coming days.

4. EXAMPLE:
• (Student result data send to you it a row data) than you ask that
• (50% student pass 50% fail… it a meaning full insight)
• (That you take decision what to do for increase passing ratio)
• Then Subject ratio…..
• Rasturant
• About product sale in market

5. Why we Need It
• 15 to 20 years later data store in excel…… data mostly 200, 300 row that easily
perceive and take decision easily..
• 1990s Then internet comes .
• Big company who know the knowledge of technologies use it mostly people can’t
use this.
• Then Facebook, YouTube, Instagram, snapchat comes those force people to use
internet(Anyone use this without deeply knowledge of this)
• automatically people increase then data increase ……. Million billion even trillions
of rows that not possible analysis …

6. Foot print
• (People interact with computer generate data)
• Refers to the trail of data you leave when using the internet.
• It includes websites you visit, emails you send, and information you submit
online. A digital footprint can be used to track a person's online activities and
devices.
• (TIKTOK VEDIOS, AUTO CORRECT OPTION)
• Which things mostly like by user.

7. STEPS TO LEARN DATA SCIENCE
1-LANGUAGES:
• Python
• BASICS (LOOPS, how to define variable,data types)
• Libraries
• Numpy
• Pandas
• manipulation and preprocessing.
• R
• (R is another programming language specifically designed for statistical analysis and data visualization)

8. STEPS TO LEARN DATA SCIENCE
2-LEARN STATISTICS:
• Basic of statistics
• Study in 11th 12th (ICS)
• To get average of the data
• For example :
• What the videos that like mostly people (MODE)
• Mean, median, mode, S.D, Var ().

9. STEPS TO LEARN DATA SCIENCE
• 3-DATA VISUALISATION:
• Visualize data in Graph, Table, charts.
• Easily perceive with diagram
• For this work two libraries in python
• Matplotib
• Seaborn

10. STEPS TO LEARN DATA SCIENCE
• 4-MACHINE LEARNING:
• Basic algorithm.
• Machine learning is a subfield of artificial intelligence (AI)
• Focuses on the development of algorithms and statistical models
• That enable computers to learn and make predictions or decisions without
being explicitly programmed to do so

11. STEPS TO LEARN DATA SCIENCE
• PROJECTS:
• DO AND UNDERSTAND.
• Website for Projects (Kaggle)

12. TOOLS
For this which tool you use don’t matter ()
• Apache
• Bigspark
• Hadoop