Kursus
Intermediate SQL Server
- MenengahTingkat Keterampilan
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In this course, you will use T-SQL, the flavor of SQL used in Microsofts SQL Server for data analysis.
Software Development
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In this course, you will use T-SQL, the flavor of SQL used in Microsofts SQL Server for data analysis.
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Master sampling to get more accurate statistics with less data.
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Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.
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Learn the practical uses of A/B testing in Python to run and analyze experiments. Master p-values, sanity checks, and analysis to guide business decisions.
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Learn techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.
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Dive into the world of machine learning and discover how to design, train, and deploy end-to-end models.
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Reshape DataFrames from a wide to long format, stack and unstack rows and columns, and wrangle multi-index DataFrames.
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Transform almost any dataset into a tidy format to make analysis easier.
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Learn to create your own Python packages to make your code easier to use and share with others.
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Learn how to build your own SQL reports and dashboards, plus hone your data exploration, cleaning, and validation skills.
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Learn Snowflake data types and functions to manipulate text, numbers, and dates while building custom functions and pivot tables.
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Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.
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This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.
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Discover Snowflake window functions to solve complex data problems with rankings, partitions, and rolling calculations.
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Build the foundation you need to think statistically and to speak the language of your data.
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In this conceptual course (no coding required), you will learn about the four major NoSQL databases and popular engines.
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Learn to implement custom trading strategies in Python, backtest them, and evaluate their performance!
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Learn to perform linear and logistic regression with multiple explanatory variables.
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Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability.
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In this course, youll learn the basics of relational databases and how to interact with them.
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Use Seaborns sophisticated visualization tools to make beautiful, informative visualizations with ease.
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Learn to implement distributed data management and machine learning in Spark using the PySpark package.
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