Course schedule
This page is under update.
- lecture;
- hands-on workshop;
- break
Before the course
Day 1
09.00 - 10.15 Introduction ad setup (Sergiu, html, notebook)
10.15 - 10.30 Break
10.30 - 10.15 Jupyter (Sergiu, jupter)
10.15 - 11.00 Python tutorial (Sergiu, tutorial)
11.00 - 11.05 short Break
11.05 - 12.00 Python, data sciene (Sergiu, tutorial)
12.00 - 13.00 Lunch
13.00 - 13.45 Visualization (Sergiu, tutorial)
13.45 - 14.30 Scientific computing (Sergiu, tutorial)
14.30 - 14.45 Break
14.45 - 15.20 Statistics (Sergiu, tutorial)
15.20 - 16.00 Optimization (Sergiu, tutorial)
09.00 - 09.20 Intro to data science (Sergiu, html, notebook)
09.20 - 09.55 Dimension Reduction: (Sergiu, What is Python?)
09.55 - 10.05 Break
10.05 - 10.15 Clustering: (Sergiu, jupter)
10.15 - 10.55 Regression: (Sergiu, tutorial)
10.55 - 11.05 short Break
11.05 - 12.00 Classification: (Sergiu, tutorial)
12.00 - 13.00 Lunch
13.00 - 13.45 Data integration: (Sergiu, tutorial)
13.45 - 14.45 Deep learning (Sergiu, tutorial)
14.45 - 15.00 Break
15.00 - 15.50 Statistical learning (Sergiu, tutorial)
15.50 - 16.00 Questions (Sergiu, tutorial)
Day 3
09.00 - 09.30 Biological data engineering (Sergiu, tutorial)
09.30 - 10.00 DevOps (Sergiu, tutorial)
10.00 - 10.10 Break
10.10 - 11.10 Workflow management (Sergiu, tutorial)
11.10 - 11.20 Break
11.20 - 12.00 Grid Computing (Sergiu, tutorial) #review
12.00 - 13.00 Lunch
13.00 - 14.00 
Distributed computing (Sergiu, tutorial)
14.00 - 14.10 Break
14.10 - 14.45 AWS (Sergiu, tutorial)
14.45 - 14.50 Break
14.50 - 15.45 acceleration (Sergiu, tutorial)
Day 4
09.00 -1600 Task Day (Sergiu, slides)
Day 5
Free day
Teachers:
Teaching assistants: