A Data Science Central Community
This Online X course will survey state-of-the-art topics in Big Data, looking at data collection (smartphones, sensors, the Web), data storage and processing (scalable relational databases, Hadoop, Spark, etc.), extracting structured data from unstructured data, systems issues (exploiting multicore, security), analytics (machine learning, data compression, efficient algorithms), visualization, and a range of applications. Each module will introduce broad concepts as well as provide the most recent developments in research.
The course will be taught by a team of world experts in each of these areas from the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL).
With backgrounds in data, programming finance, multicore technology, database systems, robotics, transportation, hardware, and operating systems, each MIT Tackling the Challenges of Big Data professor brings their own unique experience and expertise to the course.
Module One: Introduction and Use Cases
The introductory module aims to give a broad survey of Big Data challenges and opportunities and highlights applications as case studies.
Module Two: Big Data Collection
The data capture module surveys approaches to data collection, cleaning, and integration.
Module Three: Big Data Storage
The module on Big Data storage describes modern approaches to databases and computing platforms.
Module Four: Big Data Systems
The systems module discusses solutions to creating and deploying working Big Data systems and applications.
Module Five: Big Data Analytics
The analytics module covers state-of-the-art algorithms for very large data sets and streaming computation.
Prerequisite(s): This course is designed to be suitable for anyone with a bachelor’s level education in computer science. It is not free.