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#Bootcamp dat install
#Bootcamp dat how to
Milestone 1: Learn how to use Jupyter Notebooks.Identifying a problem and asking good questions.Understand the big picture and the importance of data science in industry, research and technology.Complete a data science project, end to end.Apply machine learning on a variety of datasets.Properly clean and prepare data for machine learning.Use Matplotlib and Seaborn to perform data visualization.Perform exploratory data analysis using Pandas.Interact with and manipulate data arrays and matrices using NumPy.Learn the primary libraries for data science in Python including NumPy, Pandas, Matplotlib and Scikit-learn.Understand the reasons for Python's popularity in data science.Understand foundational inferential statistics.Understand foundational descriptive statistics.Have a clear understanding of data science and its role.Install Anaconda on a personal computer.We'll discuss the various ways to measure model performance, how to select the best model for your project, and ways to refine that model.ĭuring this course, you will have the opportunity to: We will also focus on machine learning and predictive analytics.
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We will also cover descriptive and inferential statistics which will enable you to perform hypothesis testing so that you can better interpret the significance of your analysis. We'll talk about how to clean, transform, and prepare data for analysis.
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We will begin by discussing the data science process and how to effectively work through a data science problem.
#Bootcamp dat professional
In six, half-day sessions of hands-on training, you can quickly become a knowledgeable, productive, and efficient Data Science professional and earn a Stanford Technology Training Certificate of Proficiency in Data Science.