Fall 2020/2021 all materials on Microsoft teams.

This class is supported by DataCamp, the most intuitive learning platform for data science and analytics. Details will be announced soon. 

Course Information:

Teaching Assistant: Eng. Yehia Salah
 Lab detailed — schedule of tasks Tasks updated 12_11

helpful resource:
book:   Data Analytics with Hadoop
An Introduction for Data Scientists

Course Grading: (Still may be changed)

Final Exam 50 points
 Online Quiz 10 points
Midterm Exam  10 points
Lab tasks 20 points
Final task 10 Points

Course Lectures:

Lec 1 ,2  Introduction to Distributed Systems: slides_01
characterizations, Examples of distributed systems, Challenges
Lec 3 Architectures: style, Middleware organization, System architecture,
Example architectures slides2
Lec 4, 5, 6  Processes  — slides from 49-65 for reading only.
updated 15/10/2017 slides_03 (4)
Lec 7  Communication slide_04_updated 
Lec 8,9  Consistency and replication slides_07 (2)
Lec 10,11  Security slides_09 (1)

helpful videos


Lec 12 Case Study GoogleCaseStudy2 (not included in final exam)

Some resources: Google file system,  Google cloud, 

Course resources:

Books  main Textbook:
Andrew Tanenbaum and Maarten van Steen: Distributed Systems: Principles and Paradigms,  Prentice Hall; 3rd edition,  2017. other textbooks:
George Coulouris, Jean Dollimore, Tim Kindberg and Gordon Blair: Distributed Systems Concepts and Design, Fifth Edition, Fifth Edition, published by Addison Wesley, May 2011.