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Learning Path
This path is for BI Analysts or Data Scientists looking to master Python's most powerful tools for data analysis and visualization, including Pandas, Matplotlib, Seaborn, Plotly and Dash.
This path is for BI analysts or data scientists looking to build job-ready Python skills and master the most popular libraries for data analysis and visualization.
We'll start by mastering the core building blocks of Python for analytics, including data types, properties, and foundational tools like variables, numeric and string operators, conditional logic, loops and functions.
Next we'll dive into NumPy & Pandas, two of the most popular Python packages for data analysis. We'll introduce arrays and array properties, common operations like indexing, slicing, filtering and sorting, and powerful methods for exploring, analyzing, aggregating and transforming dataframes.
From there we'll explore data visualization methods using Matplotlib & Seaborn. We'll introduce data visualization frameworks and best practices, review tools and techniques for building and customizing basic charts, then explore advanced formatting options and custom visuals.
Last but not least we'll use Plotly & Dash to build and deploy interactive visuals, dashboards, and web applications.
Chris is a Python expert, certified Statistical Business Analyst, and seasoned Data Scientist, having held senior-level roles at large insurance firms and financial service companies. He earned a Masters in Analytics at NC State's Institute for Advanced Analytics, where he founded the IAA Python Programming club.
This path is for aspiring analysts and BI professionals looking to master a powerful stack of self-service business intelligence tools, including Excel, Power BI, MySQL and Tableau
This path is about bringing your data to LIFE, with project-based courses featuring some of the most popular data visualization platforms, including Excel, Power BI and Tableau
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