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Updated in [June 30th, 2023]

Foundations of Data Analysis - Part 1: Statistics Using R is a course designed to provide learners with the basics of statistical thinking. Through instructional videos, guided questions, weekly tutorials, and Pre-Labs and Labs, learners will gain an understanding of Descriptive Statistics, Modeling, and Inferential Statistics. The course will also cover the use of R, a widely available statistical software package, to answer questions about data. By the end of the course, learners will have the skills to use basic statistical techniques to answer their own questions about their own data.

[Applications]
Upon completion of this course, learners will be able to apply their knowledge of basic statistical techniques to answer their own questions about their own data, using the widely available statistical software package R. They will be able to use their new skills to make informed decisions and gain a better understanding of the world around them.

[Career Path]
One job position path recommended to learners of this course is a Data Analyst. Data Analysts are responsible for collecting, organizing, and analyzing data to help inform business decisions. They use a variety of tools and techniques, such as R, to identify trends and patterns in data sets. They also create reports and visualizations to communicate their findings to stakeholders. Data Analysts must have strong problem-solving and analytical skills, as well as a good understanding of statistics and data analysis techniques.

The demand for Data Analysts is expected to continue to grow in the coming years, as businesses increasingly rely on data-driven decision making. Companies are looking for Data Analysts who can help them make sense of the vast amounts of data they have access to, and who can help them make better decisions. As such, Data Analysts will need to stay up to date with the latest trends and technologies in the field. Additionally, Data Analysts will need to have strong communication and presentation skills, as they will be expected to present their findings to stakeholders.

[Education Path]
The recommended educational path for learners of this course is to pursue a Bachelor's degree in Data Analysis. This degree will provide learners with a comprehensive understanding of data analysis, including the fundamentals of statistics, data mining, machine learning, and data visualization. Learners will also gain an understanding of the ethical and legal implications of data analysis. The degree will also cover topics such as data management, data security, and data governance. Additionally, learners will gain the skills to develop and implement data-driven solutions to real-world problems.

The development trend of this degree is to focus on the application of data analysis in various fields, such as healthcare, finance, and marketing. This will involve the use of advanced analytics techniques, such as predictive analytics, natural language processing, and artificial intelligence. Additionally, the degree will focus on the development of data-driven decision-making skills, which will enable learners to make informed decisions based on data. Finally, the degree will also focus on the development of data-driven communication skills, which will enable learners to effectively communicate their findings to stakeholders.