Data science is the practice of solving real-world problems through data analysis and interpretation. It involves a series of steps including data collection, cleaning, modeling, and deployment, utilizing various tools and algorithms. Essential skills for data scientists include mathematics, statistics, programming, and critical thinking.

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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Data
Science
Components

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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
1. Curiosity 1. 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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