One of the principal responsibilities of a data scientist is to make reliable predictions based on data. When the amount of data available is enormous, it helps if some of the analysis can be automated. Machine learning is a way of identifying patterns in data and using them to automatically make predictions or decisions. In this data science course, you will learn basic concepts and elements of machine learning. The two main methods of machine learning you will focus on are regression and classification. Regression is used when you seek to predict a numerical quantity. Classification is used when you try to predict a category (e.g., given information about a financial transaction, predict whether it is fraudulent or legitimate). For regression, you will learn how to measure the correlation between two variables and compute a best-fit line for making predictions when the underlying relationship is linear. The course will also teach you how to quantify the uncertainty in your prediction using the bootstrap method. These techniques will be motivated by a wide range of examples. For classification, you will learn the k-nearest neighbor classification algorithm, learn how to measure the effectiveness of your classifier, and apply it to real-world tasks including medical diagnoses and predicting genres of movies. The course will highlight the assumptions underlying the techniques, and will provide ways to assess whether those assumptions are good. It will also point out pitfalls that lead to overly optimistic or inaccurate predictions.
An excellent online course offered by edX: how it works
edX courses consist of weekly learning sequences. Each learning sequence is composed of short videos interspersed with interactive learning exercises, where students can immediately practise the concepts from the videos. The courses often include tutorial videos that are similar to small on-campus discussion groups, an online textbook, and an online discussion forum where students can post and review questions and comments to each other and teaching assistants. Where applicable, online laboratories are incorporated into the course.
edX offers certificates of successful completion and some courses are credit-eligible. Whether or not a college or university offers credit for an online course is within the sole discretion of the school. edX offers a variety of ways to take courses, including verified courses where students have the option to audit the course (no cost) or to work toward an edX Verified Certificate (fees vary by course). edX also offers XSeries Certificates for completion of a bundled set of two to seven verified courses in a single subject (cost varies depending on the courses).
An edX learning programme under Other Experiences
