What is data science, and what does a data scientist do?

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Supervised and Unsupervised Learning are two primary types of machine learning, differing mainly in  The primary goal of a data science project is to extract actionable insights from data to support better decision-making, predictions, or automation—ultimately solving a specific business or real-world problem. 

Data Science is the interdisciplinary field that combines statistics, mathematics, computer science, and domain knowledge to extract meaningful insights and knowledge from structured and unstructured data. It involves collecting, cleaning, analyzing, and interpreting data to support decision-making, build predictive models, and uncover hidden patterns that can drive business or research outcomes.

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What a Data Scientist Does:

A Data Scientist is a professional who applies data science techniques to solve real-world problems. Their role typically includes:

1. Data Collection & Preparation

   • Gathering data from multiple sources (databases, APIs, sensors, etc.).

   • Cleaning and preprocessing data to handle missing values, duplicates, or inconsistencies.

2. Exploratory Data Analysis (EDA)

   • Using statistical methods and visualization to understand trends, correlations, and anomalies in data.

3. Model Building & Machine Learning

   • Designing predictive or descriptive models using algorithms such as regression, classification, clustering, or deep learning.

   • Training, testing, and fine-tuning models for accuracy.

4. Interpreting & Communicating Insights

   • Translating complex data findings into business-friendly insights through dashboards, reports, and visualizations.

   • Collaborating with stakeholders to recommend data-driven strategies.

5. Deployment & Monitoring

   • Integrating models into production systems so they can be used in real-time decision-making.

   • Monitoring performance to ensure models remain accurate over time.

6. Problem-Solving & Innovation

• Applying advanced techniques (e.g., NLP, computer vision, generative AI) to solve industry-specific challenges.

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