<p data-start="0" data-end="183">Here are some <strong data-start="14" data-end="44">good data science projects&mdash;suitable for learners and professionals alike&mdash;that cover key concepts like data cleaning, visualization, machine learning, and deployment:

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<h3 data-start="190" data-end="226">1. <strong data-start="197" data-end="226">Customer Churn Prediction</h3>
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<p data-start="229" data-end="303"><strong data-start="229" data-end="248">What it covers: Classification, feature engineering, model evaluation.

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<p data-start="306" data-end="396"><strong data-start="306" data-end="319">Use case: Predict which customers are likely to leave a service using historical data.

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<p data-start="399" data-end="448"><strong data-start="399" data-end="409">Tools: Python, scikit-learn, pandas, seaborn.

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<h3 data-start="455" data-end="483">2. <strong data-start="462" data-end="483">Sales Forecasting</h3>
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<p data-start="486" data-end="554"><strong data-start="486" data-end="505">What it covers: Time series analysis, regression, visualization.

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<p data-start="557" data-end="614"><strong data-start="557" data-end="570">Use case: Forecast future sales based on past trends.

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<p data-start="617" data-end="668"><strong data-start="617" data-end="627">Tools: Python, Prophet, ARIMA, Excel, Power BI.

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<h3 data-start="675" data-end="725">3. <strong data-start="682" data-end="725">Sentiment Analysis of Tweets or Reviews</h3>


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<p data-start="728" data-end="818"><strong data-start="728" data-end="747">What it covers: Natural Language Processing (NLP), text preprocessing, classification. Also explore Data Visualization Techniques

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<p data-start="821" data-end="896"><strong data-start="821" data-end="834">Use case: Analyze public sentiment about products, politics, or brands.

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<p data-start="899" data-end="940"><strong data-start="899" data-end="909">Tools: NLTK, TextBlob, spaCy, Python.

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