After completing the course, you will…
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Master critical data science skills.
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Understand Machine Learning from top to bottom.
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Replicate real-world situations and data reports.
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Learn NumPy for numerical processing with Python.
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Conduct feature engineering on real world case studies.
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Learn Pandas for data manipulation with Python.
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Create supervised machine learning algorithms to predict classes.
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Learn Matplotlib to create fully customized data visualizations with Python.
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Create regression machine learning algorithms for predicting continuous values.
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Learn Seaborn to create beautiful statistical plots with Python.
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Construct a modern portfolio of data science and machine learning resume projects.
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Learn how to use Scikit-learn to apply powerful machine learning algorithms.
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Get set-up quickly with the Anaconda data science stack environment.
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Learn best practices for real-world data sets.
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Understand the full product workflow for the machine learning lifecycle.
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Explore how to deploy your machine learning models as interactive APIs.
Who this course is for:
- Beginner Python developers curious about Machine Learning and Data Science with Python
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