For a start, explain to your students what machine learning is and how it works. It is wise to start with the simplest linear regression and gradient descent, then move on to the task of classification and logistic regression, to explain why the linear model do not always(almost never). Next, tell us about an ordinary fully connected mesh and better optimization techniques(sgd, momentum, etc.)
After that, your students will be ready to meet with convolutional and recurrent networks. About word embeddings(w2d, bag-of-words, tf-idf etc.) you can tell right in the course.
tasks designed for students in grades 10-11 and students of 1-2 courses.
3) lab RNN: 1
is a very clear about the recurrent network.
5) CNN in NLP: 1
- in simple language about complicated things.