Big Data Fundamentals

Organisations now have access to massive amounts of data and it’s influencing the way they operate. They are realising in order to be successful they must leverage big data insights to make effective business decisions. What will you learn? In this big data fundamentals course, part of the Big Data MicroMasters program, you will learn how big data is driving organisational change and the key challenges organisations face when trying to analyse massive data sets. You will learn fundamental techniques, such as data mining and stream processing. You will also learn how to design and implement PageRank algorithms using MapReduce, a programming paradigm that allows for massive scalability across hundreds or thousands of servers in a Hadoop cluster. You will learn how big data has improved web search and how online advertising systems work. By the end of this course, you will have a better understanding of the various applications of big data methods and big data insights in industry and research. Who should study this big data course? This course forms part of the Big Data MicroMasters Program, which provides existing or aspiring data scientists and business analysts with the the skills to make informed, data-driven business decisions. 3b

• Knowledge and application of MapReduce
• Understanding the rate of occurrences of events in big data
• How to design algorithms for stream processing and counting of frequent elements in Big Data
• Understand and design PageRank algorithms
• Understand underlying random walk algorithms

• Yes. Candidates interested in pursuing the MicroMasters program in Big Data are advised to complete Programming for Data Science and Computational Thinking and Big Data before undertaking this course.Visit the MicroMasters Big Data Program page for more information.