Lectures
Lectures are on Fridays at 12.15 - 14.00 in J. Liivi 2 - 122
- 07.09 - Lecture 1: Introduction to the course; Cloud overview and Data Analytics (Satish Srirama)
- 14.09 - Lecture 2: Introduction to MapReduce (Satish Srirama)
- 21.09 - Lecture 3: MapReduce Algorithms (Satish Srirama)
- 28.09 - Lecture 4: MapReduce in Information Retrieval (Satish Srirama)
- 05.10 - * NO session - Due to ICS Day
- 12.10 - Lecture 5: Graph Data Processing with MapReduce (Satish Srirama)
- 19.10 - Lecture 6: Joins with MapReduce and MapReduce limitations (Satish Srirama)
- 26.10 - Lecture 7: Higher level scripting languages for distributed data processing (Pelle Jakovits)
- 02.11 - Lecture 8: In-memory data processing (Pelle Jakovits)
- 09.11 - Lecture 9: SQL abstraction for distributed data processing (Pelle Jakovits)
- 16.11 - Lecture 10: DataFrame abstraction for distributed data processing (Pelle Jakovits)
- 23.11 - Lecture 11: Distributed Stream Data Processing (Pelle Jakovits)
- 30.11 - Lecture 12: Distributed Graph processing with BSP, Pregel and DataFrames (Pelle Jakovits)
- 07.12 - Lecture 13: Non-Relational databases​ (Pelle Jakovits)
- 14.12 - Lecture 14: Distributed Machine Learning​ in Hadoop Ecosystem (Pelle Jakovits)