Data science is the study of data to extract meaningful insights for business. Data science uses the most powerful hardware, programming systems, and most efficient algorithms to solve the data related problems. It is the future of artificial intelligence.

1. DATA SCIENCE
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2. 12. Iterative
Process
1. Data
Collection
10. Monitoring &
Maintaninance
2. Data
Cleaning &
Preprocess
5. Model
Building
9. Deployment
11. Interpretation
& Communication
8. Model
Tuning
3. EDA
4. Feature
Engineering
6. Training
& Testing
7. Model
Evaluation
Data Science
Life Cycle
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Dat
a
Science
Component
s

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What is
Data
Science?
Needs of
Data
Science
Prerequisite
of Data
Science
Solving
Problem
With Data
Science
Data
Science
Tools
Data
Science
Jobs
Data
Science
Application
Data Science Tutorial
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Data science is the art of using data to solve real-world
problems and make informed decisions by analyzing and
interpreting information from various sources.
What is Data
Science?

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Math &
Statistics Team Player
Skill
Communica
-tion Skill
Coding &
Programming
Skills

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Technical Non-Technical
Prerequisite For Data
Science
2. Critical Thinking
3. Communication Skills
• Curiosity • Machine
Learning
2. Mathematical Modeling
3. Statistics
4. Computer Programming
5. Database

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Is this different?
Is this A or B? Classification Algorithm
Anomaly detection Algorithm
How much or How many? Regression Algorithm
Clustering Algorithm
How is this organized
What should I do next? Reinforcement Learning
Possible Questions Applicable Algorithms
Solving Problems in Data Science with ML

9. Data Science
Tools
• Data Analysis tools
• Data Warehousing
• Data Visualization
• Machine Learning Tools
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2. Data Analyst
1. Data Scientist
3. Machine Learning Expert
4. Data Engineer
5. Data Architect
6. Data Administrator
7. Business Analyst
8. Business Intelligence Manager

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Data Science
Applications

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THANK YOU
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