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Complete all chapters to get certificate
Let's take a look at what we'll be working with in this course. The first section will acquaint you with Python, a flexible and advanced programming language known for its clear syntax and readability.
NumPy is a fundamental library in Python that facilitates efficient numerical computations with powerful n-dimensional arrays and mathematical functions.
Pandas provides intuitive and versatile data structures for efficient data manipulation and analysis, streamlining the initial stages of the data science pipeline.
Seaborn is a Python data visualization library based on Matplotlib that provides a high-level interface for creating informative and attractive statistical graphics.
Statistics provides data scientists with foundational techniques and tools to extract meaningful insights from data, allowing them to make informed decisions and predictions based on empirical evidence.
Scikit-learn is an open-source Python library that provides simple and efficient tools for data analysis and modeling, particularly for machine learning. Data scientists use it extensively for its comprehensive collection of algorithms and processing techniques, enabling them to quickly develop and deploy predictive models.