diff --git a/doc/LectureNotes/schedule.md b/doc/LectureNotes/schedule.md
index fc188fae5..b41450605 100644
--- a/doc/LectureNotes/schedule.md
+++ b/doc/LectureNotes/schedule.md
@@ -114,7 +114,7 @@ For the reading assignments we use the following abbreviations:
 - Lecture Thursday: Deep learning and Neural Networks, developing a code for Neural Networks
   - Video of Lecture at https://youtu.be/yzbxJI6LgL0
 - Lecture Friday: Tensorflow and the mathematics of neural network
-  - Video of Lecture at 
+  - Video of Lecture at https://youtu.be/CPj4mh7M9no
 - Reading recommendations:
   - See lecture notes for week 41 at https://compphysics.github.io/MachineLearning/doc/web/course.html.
   - For neural networks we recommend Goodfellow et al chapters 6 and 7. For CNNs, see Goodfellow et al chapter 9. chapter 11 and 12 on practicalities and applications
diff --git a/doc/src/week41/week41.do.txt b/doc/src/week41/week41.do.txt
index 579279ec3..1bb542c5c 100644
--- a/doc/src/week41/week41.do.txt
+++ b/doc/src/week41/week41.do.txt
@@ -9,7 +9,8 @@ DATE: today
 * Thursday: Building our own Feed-forward Neural Network and discussion of project 2.
   * "Video of lecture":"https://youtu.be/yzbxJI6LgL0"
 * Friday: Playing around with our own Feed-forward Neural Network and introduction to TensorFlow. Solving differential equations with neural networks. 
-
+  * "Video of lecture":"https://youtu.be/CPj4mh7M9no
+"
 Reading suggestions for both days: These notes, "Aurelien Geron's chapters 10-11":"https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf".
 For a more in depth discussion on  neural networks we recommend Goodfellow et al chapters 6 and 7. Bishop's chapter 5 on Neural Networks is an additional good read.