Course Length 4 hours 0 minute
Data preparation, data cleaning, data preprocessing (whatever you want to call it) is quite often the most tedious and time-consuming work in the data science/data analysis area. Especially if we are short of time and want to deliver crucial data analysis insights to our audience.
KNIME makes the data prep process efficient and easy. With KNIME, you can use the easy-to-use drag-and-drop interface, if you are not an experienced coder. But if you know how to work with languages such as R, Python, or Java, you can use them as well. This makes KNIME a truly flexible and versatile tool.
In this course, we will learn the efficient ways to import multiple files into KNIME, loops, web scraping, scripting (using Python code in KNIME), hyperparameter optimization, and feature selection. Also, learn basic machine learning workflows and helpful nodes for this in KNIME.
By the end of this course, you will be able to use KNIME for data cleaning and data preparation without any code.
All the resources and support files for this course are available at https://github.com/PacktPublishing/Data-science-and-Data-preparation-with-KNIME
Dan We is a 31-year-old entrepreneur, data scientist, and data analytics/visual analytics consultant. He holds a master’s degree and is certified in Power BI as a qualified associate in Tableau. He is currently working in business intelligence and helps major companies get key insights from their data to deliver long-term growth and outpace their competitors.
He is committed to support other people by offering them educational services to help them accomplish their goals and become the best in their profession or explore a new career path.