KNIME for Data Science and Data Cleaning

Description

In this course, you will learn how to perform data cleaning and data preparation with KNIME and without coding. You should be familiar with KNIME as no basics are covered in this course. Basic knowledge of machine learning is certainly helpful for the later lectures in this course.

Data cleaning is always a big hassle, especially if we are short on 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 how to use additional helpful KNIME nodes not covered in the other two classes. Solve data cleaning challenges together for different datasets. Use pre-trained models in TensorFlow in KNIME (involves Python coding). Also, learn the fundamentals for NLP tasks (Natural Language Processing) in KNIME using only KNIME nodes (without any additional coding). 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/KNIME-for-Data-Science-and-Data-Cleaning

How to use TensorFlow in KNIME
How to do data science in KNIME with and without coding
How to solve data cleaning and data preparation challenges
How to replace Excel and start KNIME for ETL and data cleaning issues
Examples of data science machine learning workflows with KNIME

This course is designed for aspiring data scientists and data analysts who want to work smarter, faster, and more efficiently. This course is also for anyone who wants to learn how to effectively clean data or encounter various data issues (for example, format) in the past and is looking for a solid solution, and who is familiar with KNIME as no basics are covered in this course. Basic knowledge of machine learning is certainly helpful for the later lectures in this course. Note: Tableau Desktop and Microsoft Power BI Desktop are optional.

This course is practical and consists of a case study where you can and should follow along to solve tasks.

No coding required * Solve data cleaning challenges together and enhance your basic KNIME skills * Learn the fundamentals for NLP tasks in KNIME using only KNIME nodes

https://github.com/PacktPublishing/KNIME-for-Data-Science-and-Data-Cleaning

Dan We is a 32-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 in order to deliver long-term growth and outpace their competitors. He is committed to supporting 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.

1. Einleitung

2. Older videos KNIME version before 4.3