2020 Cloud Computing and Big Data Final Lecture 16 Epilogue 💻
2020 Cloud Computing and Big Data Final Lecture 16 Epilogue 💻
Parallel & Scalable Machine Learning & Deep Learning
16 university lectures with additional practical lectures for hands-on exercises in context
University of Iceland, School of Engineering and Natural Sciences
Faculty of Industrial Engineering, Mechanical Engineering and Computer Science
Fall 2020
Course Outline
1. Cloud Computing & Big Data Introduction
2. Machine Learning Models in Clouds
3. Apache Spark for Cloud Applications
4. Virtualization & Data Center Design
5. Map-Reduce Computing Paradigm
6. Deep Learning driven by Big Data
7. Deep Learning Applications in Clouds
8. Infrastructure-As-A-Service (IAAS)
9. Platform-As-A-Service (PAAS)
10. Software-As-A-Service (SAAS)
11. Big Data Analytics & Cloud Data Mining
12. Docker & Container Management
13. OpenStack Cloud Operating System
14. Online Social Networking & Graph Databases
15. Big Data Streaming Tools & Applications
16. Epilogue
Lecture Outline:
Cloud Computing & Big Data from another Perspective
Further Readings & Jobs Reviews
Master & Ph.D. Thesis Topics Available
High Performance Computing (HPC) Course Spring 2021
Acknowledgements & Upcoming Events
Informal final lecture:
Answering remaining questions & guidance to future topics
Summary & preparation for final exam and quizzes debrief
Mindset:
Discussion of job offers on the market in the light of the course
What we have learned & how to turn knowhow into action
Skillset:
Knowledge of various Cloud system techniques & parallel computing skills
PHD positions & Master Thesis topics HPC/Cloud and/or Machine & Deep Learning
Toolset:
Knowledge of services in real Clouds (AWS, MS Azure, Google Colab, HDF) & machine/deep learning libraries, including own cloud deployment tools (OpenStack)
Future Topics to study: Quantum computing, neural networks on the chip, neuromorphic computing, modular supercomputing, etc.