Introduction to Typeform

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This course provides an introduction to Typeform, a popular online form and survey tool. Participants will learn how to create engaging forms and surveys using Typeform's user-friendly interface, as well as how to customize the design and layout to suit their needs. The course will cover the various features and functionalities of Typeform, including logic jumps, question branching, and data analysis. Participants will also learn how to integrate Typeform with other platforms and tools to streamline their data collection and analysis processes. By the end of the course, participants will have the skills and knowledge to create effective and visually appealing forms and surveys using Typeform.

Introduction to SPSS

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This course provides an introduction to the Statistical Package for the Social Sciences (SPSS), a widely used software for statistical analysis. Students will learn the fundamental features and functions of SPSS, including data management, data entry, data analysis, and data presentation. The course will also cover basic statistical procedures, such as descriptive statistics, hypothesis testing, and data visualization. Through hands-on activities and practical exercises, students will gain the skills and knowledge needed to use SPSS to analyze and interpret data for research and decision-making purposes. No prior experience with SPSS is required.

Introduction to R Programming

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This course provides an introduction to the R programming language, a powerful tool for statistical analysis and data visualization. Students will learn the basics of R programming, including data types, functions, and packages. They will also explore how to import and manipulate data, create visualizations, and perform statistical analysis using R. By the end of the course, students will have a solid foundation in R programming and will be able to apply their skills to solve real-world data analysis problems. This course is suitable for beginners with no prior programming experience.

Data Science Full Course: Data Sourcing, Coding, Mathematics, and Statistics

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This comprehensive course covers all aspects of data science, including data sourcing, coding, mathematics, and statistics. Students will learn how to gather and clean data from various sources, manipulate and analyze it using programming languages such as Python and R, and apply statistical and mathematical techniques to derive meaningful insights. By the end of the course, students will have a thorough understanding of the entire data science process, from raw data collection to advanced analysis and visualization. This course is perfect for anyone looking to pursue a career in data science or expand their knowledge in the field.