Big businesses need high-end tools and technology to drive business insights and perform critical data analysis, developing predictive models. Data Science helps businesses manage large sets of data, using different algorithms and mathematical analysis for extracting valuable insights to apply strategic decisions.
Hands-on experience setting up an integrated analysis environment for doing data science with Python.
An understanding of how to use the Python standard library to write programs, access the various data science tools, and document and automate analytic processes.
Orientation to some of the most powerful and popular Python libraries for data science including Pandas (data preparation, analysis, and modeling; time series analysis), scikit-learn (machine learning), and Matplotlib and Seaborn (data visualization).
Working knowledge of the Python tools ideally suited for data science tasks, including:
1.Accessing data (e.g., text files, databases)
2.Cleansing and normalizing data
3.Exploring data (e.g., simple statistics, correlation matrices, visualization)
4.Modeling data (e.g., machine learning)
Data Scientist/ Data Analytics
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