UC Berkeley School of Information has a great course, where UC Berkeley professors and Twitter engineers are lectureing on the most cutting-edge algorithms and software tools for data analytics as applied to Twitter microblog data. Topics include applied natural language processing algorithms such as sentiment analysis, large scale anomaly detection, real-time search, information diffusion and outbreak detection, trend detection in social streams, recommendation algorithms, and advanced frameworks for distributed computing.
Bill Graham (@billgraham), who is active in the Hadoop community and a Pig contributor, gave a very clear and detailed intro to Hadoop and outlined how it is used at Twitter. His slides can be found here.

Follow the course on :
UC Berkeley Course Lectures: Analyzing Big Data with Twitter