unpdate schedule

Author: eotp

schedule.md

@@ -1,69 +1,71 @@
 # Workshop timeline
 
-## Introduction
+## Welcome
 
-09:30 - 09:35 Get everyone connected -- 5 Minutes
+09:30 - 09:35 Get everyone connected -- 5 Minutes `@JK`
 
-09:35 - 09:45 Welcoming by Prof. Falk Schwendicke -- 10 Minutes
+09:35 - 09:45 Welcoming by Prof. Falk Schwendicke -- 10 Minutes `@FS`
 
-09:45 - 09:50 [(simplified) Schedule](./schedule_simplified.md) and [WebEx walktrough](./webex_walkthrough.md) -- 5 Minutes
+## Introduction and Lecture/Exercise 0
 
-09:50 - 10:20 present yourself 3 minutes per breakout room -- 10 & 20 Minutes
+09:45 - 09:50 [(simplified) Schedule](./schedule_simplified.md) and [WebEx walktrough](./webex_walkthrough.md) -- 5 Minutes `@JK`
+
+09:50 - 10:20 present yourself 3 minutes per breakout room -- 10 & 20 Minutes `@JK`
 
 ## Technical setup and Lecture/Exercise #1
 
-10:20 - 11:00 Lecture #1 -- 40 Minutes
+10:20 - 11:05 Lecture #1 -- 45 Minutes `@JK`
 
-11:00 - 11:05 Launching DLI -- 5 Minutes
+11:05 - 11:10 Launching DLI -- 5 Minutes `@JK`
 
-**11:05 – 11:20 Break**
+**11:10 – 11:25 Break**
 
-11:20 – 11:25 Introduction to DLI platform -- 5 Minutes
+11:25 – 11:30 Introduction to DLI platform -- 5 Minutes `@JK`
 
-11:25 – 11:55 Introduction to Jupyter Lab and Python -- 20 Minutes
+11:30 – 12:00 Introduction to Jupyter Lab and Python -- 20 Minutes `@JK`/ _if late someone else please, as I have to get to another meeting at 12:00_
 
-11:55 – 12:15 Exercise #1 -- 20 Minutes
+12:00 – 12:40 Exercise #1 -- 40 Minutes 
 
-## Lecture/Exercise #2
+**12:40 – 13:30 Lunch break**
 
-12:15 – 13:00 Lecture #2 -- 45 Minutes
+## Lecture/Exercise #2
 
-**13:00 – 13:50 Lunch break**
+13:30 – 14:15 Lecture #2 -- 45 Minutes `@JC`
 
-13:50 – 14:10 Exercise #2 -- 20 Minutes
+14:15 – 14:50 Exercise #2 -- 35 Minutes
 
-14:10 – 14:15 Q&A -- 5 Minutes
+14:50 – 14:55 Q&A -- 5 Minutes
 
 ## Lecture/Exercise #3
 
-14:15 - 14:45 Lecture #3 -- 30 Minutes
+14:55 - 15:25 Lecture #3 -- 30 Minutes `@TBA`
 
-14:45 - 15:05 Exercise #3 -- 20 Minutes
+15:25 - 15:55 Exercise #3 -- 30 Minutes
 
 ## Lecture/Exercise #4
 
-15:05 - 15:20 Lecture #4 -- 15 Minutes
+15:55 - 16:10 Lecture #4 -- 15 Minutes `@TBA`
 
-15:20 - 15:55 Exercises #4a + 4b -- 25 Minutes
+16:10 - 16:45 Exercises #4a + 4b -- 35 Minutes
 
-15:55 – 16:00 Q&A -- 5 Minutes
+16:45 – 16:50 Q&A -- 5 Minutes
 
-**16:00 – 16:15 Break**
+**16:50 – 17:05 Break**
 
 ## Lecture/Exercise #5
 
-16:15 - 16:25 Lecture #5 -- 10 Minutes
+17:05 - 17:15 Lecture #5 -- 10 Minutes `@TBA`
 
-16:25 - 16:55 Exercises #5a + 5b -- 20 Minutes
+17:15 - 17:40 Exercises #5a + 5b -- 25 Minutes
 
-16:55 - 17:00 Q&A -- 5 Minutes
+17:40 - 17:45 Q&A -- 5 Minutes
 
 ## (optional) Lecture/Exercise #6
 
 Lecture #6 -- 20 Minutes
 
 Exercise #6 -- 20 Minutes
 
-## Assessment
+## (optional) Assessment
 
-17:00 - 17:30 Assessment + Q&A + Breakout Sessions -- 30 Minutes
+Assessment  -- 30 Minutes

schedule_simplified.md

@@ -1,12 +1,12 @@
 
 
-* 09:30 - 10:20 Introduction
-* 10:20 – 12:15 Lecture/Exercise #1: An introduction to deep learning
-* 12:15 – 13:00 Lecture #2: How a neural network train
-* 13:00 – 13:50 Lunch break
-* 13:50 – 14:15 Exercise #2
-* 14:15 – 15:05 Lecture/Exercise #3: Convolutional neural networks
-* 15:05 – 16:15 Lecture/Exercise #4: Data augmentation and deployment
-* 16:15 – 17:00 Lecture/Exercise #5: Pre-trained models
-* 17:00 – 17:30 Final project
+* 09:30 - 10:20 Welcome and introduction
+* 10:20 – 12:40 Lecture/Exercise #1: An introduction to deep learning & Introduction to Python
+* 12:40 – 13:30 Lunch break
+* 13:30 – 14:55 Lecture/Exercise #2: How a neural network train
+* 14:55 – 15:55 Lecture/Exercise #3: Convolutional neural networks
+* 15:55 – 16:50 Lecture/Exercise #4: Data augmentation and deployment
+* 17:05 – 17:30 Lecture/Exercise #5: Pre-trained models
+* (optional) Lecture/Exercise #6: NLP
+* (optional) Final project