Johns Hopkins University 3 credits Government
Machine learning (ML) and, more broadly, arti?cial intelligence can now be used to perform complex tasks in data science and social science. This course introduces students to a variety of these machine learning techniques. Students will learn the fundamentals of statistical software used for ML and develop an understanding of statistical and mathematical foundations of ML. Students will implement these techniques using open source tools in R and Python. Further, students will learn how to select an appropriate ML tool depending on the dataset they have and the question to be answered. Prerequisites: 470.681, Introduction to Data Analytics and Policy; 470.768 Programming and Data Management (470.768 may be taken concurrently with 470.667) Prerequisite(s): 470.681 Introduction to Data Analytics and Policy and 470.768 Programming and Data Management (470.768 may be taken concurrently with 470.667).
Our subject experts help with essays, research papers, case studies, discussion posts, and capstone projects for these programs β written from scratch to your course requirements.
Program and course information is reproduced from each university's published academic catalog for informational purposes and may change. Always confirm current requirements with your university. We are an independent academic support service and are not affiliated with or endorsed by the universities listed.
Expert guides on essay writing, citation styles, study skills, and academic success.
View All Articles
Learn how to write a good research question for a paper. Narrow your topic, identify a research problem, and create a focused question with practical examples.
Learn how to choose a research topic you can actually research. Discover how to narrow broad ideas, find reliable sources, and develop a focused research question.
Learn how to cite sources in a research paper using APA, MLA, and Chicago styles, with in-text citation examples and reference-list tips.