Code-Alongs
What is a Code-Along?
Code-Alongs are live experiences taught by our instructors designed to prepare you for concepts found in the sprint challenges. They're your opportunity to work on complex job-ready problems in a live and engaging environment.
These sessions are 50 minutes in length and are offered seven days a week in the morning, afternoon, and evening. Because Code-Alongs delve deeper into a core competency, you will need to come to class prepared to have the best experience.
Ideal Code-Along Preparation Checklist
- Did you review the core competencies?
- Did you watch the guided projects?
- Did you finish your module projects?
Code-Along 1: Architect and Train Neural Networks
This code-along focuses on architecting and training neural networks, reinforcing concepts from Modules 1 and 2. You'll work through realistic examples of building neural network architectures and training them effectively using Keras.
How to Prepare
- Review neural network architecture concepts from Module 1
- Review training and optimization concepts from Module 2
- Watch the guided project videos
- Complete your module projects before attending
Code-Along 2: Tune and Regularize Neural Networks
This session focuses on tuning hyperparameters and implementing regularization techniques, providing hands-on practice with concepts from Modules 3 and 4.
How to Prepare
- Review hyperparameter tuning concepts from Module 3
- Review regularization and deployment concepts from Module 4
- Watch the guided project videos
- Complete your module projects before attending
Prepare for Success
The best Code-Along experiences happen when you are ready before coming to class. Your instructors created a starting point and a solution for each of your Code-Alongs to ensure you have what you need to succeed.
Make sure to review the relevant module materials before attending the code-along. This will help you get the most out of the session and be better prepared to tackle the challenges.
Additional Resources
Neural Network Fundamentals
- Keras: The Sequential Model Guide
- TensorFlow: Basic Classification Tutorial
- 3Blue1Brown: But what is a Neural Network?
- TensorFlow: Keras Loss Functions Documentation
Training and Optimization
- TensorFlow: Keras Optimizers Documentation
- 3Blue1Brown: Gradient Descent, How Neural Networks Learn
- How to Configure the Learning Rate