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Their primary responsibilities include: Data Collection and Preparation Data Scientists start by gathering relevant data from various sources, including databases, APIs, and online platforms. They clean and preprocess the data to remove inconsistencies and ensure its quality. Big Data Technologies: Hadoop, Spark, etc.

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Kaggle datasets) and use Python’s Pandas library to perform data cleaning, data wrangling, and exploratory data analysis (EDA). Extract valuable insights and patterns from the dataset using data visualization libraries like Matplotlib or Seaborn. CNN) and classify images from a large dataset (e.g.,

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The Data Dilemma: Exploring the Key Differences Between Data Science and Data Engineering

Top 15 Data Analytics Projects in 2023 for beginners to Experienced

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