Here is my review of Mar-Apr 2015 Coursera incarnation of Text Retrieval and Search Engines, which is the second course in Data Mining specialization. It has mixed rankings, while I passed with 97.5% grade. Technologies: Search is a critical area of modern software giants like Google, Microsoft, Yahoo, Yandex, Baidu etc. The course discusses various aspects of natural language processing (NLP) and search. It touches on PageRank, Google file system (GFS), and MapReduce processing for big text data. Homework assignments introduce MeTa toolkit + some homework is done in C++. Material: The basic ideas of efficient information indexing, storage, retrieval and ranking are presented with the emphasize on applications. Course discusses vector space and probabilistic text retrieval models based on a bag of words concept. Advanced topics include ranking based on links, user feedback, and big text data. Homework includes programming competition for the best ranking algorithm implemented by a student within MeTa. Instructor/lectures: ChengXiang Zhai is a prominent researcher in Information Retrieval and Natural Language Processing. He worked in the industry as a Research Scientist. Lectures are well structured thanks to the central slide presenting the course topics.