Data Science ppt
                     Data Science 
Data science is the field of analyzing and interpreting complex data to inform 
decision-making and drive innovation. It combines techniques from statistics, 
machine learning, and data visualization to extract insights from large 
datasets. Data scientists use tools like Python, R, and SQL to turn data into 
actionable intelligence.
Types of data science
Here are the main types of data science roles, briefly summarized:
1. Data Analyst: Focuses on interpreting data, creating reports, and visualizing trends.
2. Data Scientist: Develops models and algorithms to predict outcomes and extract 
insights.
3. Machine Learning Engineer: Designs and implements machine learning models and 
systems.
4. Data Engineer: Builds and maintains data pipelines and infrastructure.
5. Business Intelligence (BI) Developer: Creates data models and dashboards to support 
business decisions.
6. Statistical Analyst: Applies statistical methods to analyze and interpret complex data.
Each type specializes in different aspects of working with data to drive informed 
decisions.

Feature of data science
 Key features of data science include:
1. Data Collection: Gathering data from various sources.
2. Data Cleaning: Processing and preparing data for analysis.
3. Exploratory Analysis: Identifying patterns and trends in data.
4. Model Building: Developing algorithms and predictive models.
5. Visualization:  Creating charts and graphs to represent data insights.
6. Statistical Analysis: Applying statistical techniques to interpret data.
7. Machine Learning: Using algorithms to improve predictions and automate 
decisions.
8. Data Interpretation: Drawing actionable conclusions from data findings.
Scop of data science
 The scope of data science includes:
1. Predictive Analytics: Forecasting future trends based on historical data.
2 Data Visualization: Creating visual representations to make data insights accessible.
3. Machine Learning: Developing algorithms for automated decision-making and pattern 
recognition.
4.Big Data Analytics: Analyzing large and complex datasets to uncover hidden patterns.
5. Data Engineering: Building and optimizing data pipelines and infrastructure.
6. Business Intelligence: Generating actionable insights to support strategic decisions.
7. Statistical Analysis: Applying statistical methods to understand data and validate models. 
 Data science applies to various industries, including finance, healthcare, marketing, and 
technology.

Salary in data science
Salaries for data science roles in India vary by experience and location. Here’s a general 
overview:
1. Entry-Level Data Scientist:₹6,00,000 - ₹10,00,000 per year
2.Mid-Level Data Scientist: ₹10,00,000 - ₹18,00,000 per year
3. Senior Data Scientist: ₹18,00,000 - ₹30,00,000+ per year
4. Data Science Manager:₹25,00,000 - ₹40,00,000+ per year
5. Chief Data Officer (CDO): ₹40,00,000 - ₹60,00,000+ per year
Salaries can vary based on factors such as the company's size, industry, and geographic 
location, with tech hubs like Bangalore, Mumbai, and Delhi often offering higher packages.
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