This course on SPSS: Cleaning and Preparing Your Data For Accurate Analyses is designed to help new learners understand the importance of data cleaning and preparing data for accurate analyses. It provides step-by-step examples, PowerPoint slides, and other helpful supporting materials to help learners gain the technical skills needed to conduct rigorous research studies. It is suitable for doctoral students, undergraduate students, early career researchers, and those who wish to learn about the process of data cleaning. Learn how to anticipate cleaning before or during collection, understand why not all missing data are the same, the importance of recording the cleaning process and decisions, and what part of cleaning to report in a manuscript. Click now to get started!

This course provides learners with the skills and knowledge necessary to clean and preprocess data in Python for Machine Learning. It covers a range of data cleaning techniques, such as imputing missing values, feature scaling, fixing data types issues, and more. Through lectures, quizzes, and Jupyter notebooks, learners will gain the skills to deal with real world raw data and be able to detect and remove outliers, clean and preprocess textual data for NLP, and use the Apply Lambda method for advanced cleaning functions. Click this course to gain the skills and knowledge to clean and preprocess data in Python for Machine Learning.

This course provides learners with an in-depth understanding of data cleaning techniques in Data Science & Machine Learning. It covers topics such as data reading, merging or splitting datasets, different visualization tools, locating or handling missing/absurd values, and hands-on sessions. By enrolling in this course, learners will gain the knowledge and skills necessary to effectively clean data for Data Science & Machine Learning. They will also understand why data cleaning is important, and how it can improve decision making, efficiency, and productivity. Learners will have the opportunity to practice their data cleaning skills with a dataset. This course is perfect for new learners who want to gain a comprehensive understanding of data cleaning techniques in Data Science & Machine Learning.

This course is perfect for new learners who want to learn the basics of data cleaning, data exploration and data analysis in SAS and R. It provides downloadable sample codes of SAS and R that students can copy, paste and run in the appropriate software. Step-by-step activities are included in the form of lectures, demos and PowerPoint presentations with annotations describing procedures, functions and options in SAS Studio, and functions in RStudio. Basic knowledge in at least one programming language (SAS or R) is required to take this course. Click now to get started on your journey to mastering data analysis with SAS and R!