Python Data Science with Pandas: Master 12 Advanced Projects. Work with Pandas, SQL Databases, JSON, Web APIs & more to master your real-world Machine Learning & Finance ProjectsThis Course starts where many other courses end: You can write some Pandas code but you are still struggling with real-world Projects because
- Real-World Data is typically not provided in a single or a few text/excel files -> more advanced Data Importing Techniques are required
- Real-World Data is large, unstructured, nested and unclean -> more advanced Data Manipulation and Data Analysis/Visualization Techniques are required
- many easy-to-use Pandas methods work best with relatively small and clean Datasets -> real-world Datasets require more General Code (incorporating other Libraries/Modules)
Python Data Science with Pandas: Master 12 Advanced Projects Description
Contents
Requirements
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You should be familiar with Python (Standard Library, Numpy, Matplotlib)
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You should have worked with Pandas before (at least you should know the basics)
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A desktop computer (Windows, Mac, or Linux) capable of storing and running Anaconda. The course will walk you through installing the necessary free software.
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An internet connection capable of streaming HD videos.
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Some high school level math skills would be great (not mandatory, but it helps)
What you’ll learn
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Advanced Real-World Data Workflows with Pandas you won´t find in any other Course.
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Working with Pandas and SQL-Databases in parallel (getting the best out of two worlds)
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Working with APIs, JSON and Pandas to import large Datasets from the Web
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Bringing Pandas to its Limits (and beyond…)
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Machine Learning Application: Predicting Real Estate Prices
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Finance Applications: Backtesting & Forward Testing Investment Strategies + Index Tracking
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Feature Engineering, Standardization, Dummy Variables and Sampling with Pandas
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Working with large Datasets (millions of rows/columns)
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Working with completely messy/unclean Datasets (the standard case in real-world)
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Handling stringified and nested JSON Data with Pandas
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Loading Data from Databases (SQL) into Pandas and vice versa
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Loading JSON Data into Pandas and vice versa
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Web-Scraping with Pandas
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Cleaning large & messy Datasets (millions of rows/columns)
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Working with APIs and Python Wrapper Packages to import large Datasets from the Web
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Explanatory Data Analysis with large real-world Datasets
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Advanced Visualizations with Matplotlib and Seaborn
Who this course is for:
- Everyone who really want to master large, messy and unclean Datasets.
- Everyone who want to improve skills from “I can write some Pandas Code” to “I can master my real-word Data Projects with Pandas”
- Data Scientists
- Machine Learning Professionals
- Finance & Investment Professionals
- Researchers
