Syllabus and Course Schedule

Time and Location: Wed 11:30 AM - 12:50 PM, NVIDIA Auditorium
Past schedules: (Spring 2018) (Winter 2018) (Fall 2017)
For all "Materials and Assignments", follow the deadlines listed on this page, not on Coursera! Assignments are usually due every Wednesday, 30min before the class starts

EventDateDescriptionMaterials and Assignments
Neural Networks and Deep Learning (Course 1)
Lecture 1 09/26 Advanced Lecture Topics:
  • AI is the new electricity
  • Details of the course
Handouts
Lecture 2 10/03 Advanced Lecture Topic: Deep Learning Intuition
  • How to frame a machine learning problem?
  • How to choose your loss function?
  • Intuition behind various real-world application of deep learning.
Completed modules:
  • C1M1: Introduction to deep learning
  • C1M2: Neural Network Basics
Handouts Required:
  • Find partner(s) for your final project and sign up here (link coming soon)
Quizzes (due at 11am):
  • Introduction to deep learning
  • Neural Networks Basics
Programming Assignments (due at 11am)
  • Python Basics with Numpy (Optional)
  • Logistic Regression with a neural network mindset
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization (Course 2)
Lecture 3 10/10 Advanced Lecture Topic:
  • Full-Cycle of a deep learning project
  • The Mathematics of Deep Learning (backpropagation, initialization, regularization)
Completed modules:
  • C1M3: Shallow Neural Network
  • C1M4: Deep Neural Networks
Handouts Quizzes (due at 11am):
  • Shallow Neural Networks
  • Key concepts on Deep Neural Networks
Programming Assignments (due at 11am):
  • Planar data classification with a hidden layer
  • Building your Deep Neural Network: step by step
  • Deep Neural Network - Application
Project Proposal Due 10/14
Sunday
11:59PM
Lecture 4 10/17 Advanced Lecture Topics:
  • Attacking neural networks with Adversarial examples
  • Generative Adversarial Networks
Completed modules:
  • C2M1: Practical aspects of deep learning
  • C2M2: Optimization algorithms
Handouts Optional Video
  • Batch Normalization videos from C2M3 will be useful for the in-class lecture.
Optional Reading Quizzes (due at 11am):
  • Practical aspects of deep learning
  • Optimization Algorithms
Programming Assignments (due at 11am):
  • Initialization
  • Regularization
  • Gradient Checking
  • Optimization
Structuring Machine Learning Projects (Course 3)
Lecture 5 10/24 Advanced Lecture Topics:
  • AI in Health Care (Guest Speaker: Pranav Rajpurkar)
  • Live-cell segmentation Case Study
Completed modules:
  • C2M3: Hyperparameter Tuning, Batch Normalization
  • C3M1: ML Strategy (1)
  • C3M2: ML Strategy (2)
Handouts Optional Reading Quizzes (due at 11am):
  • Hyperparameter tuning, Batch Normalization, Programming Frameworks
  • Bird recognition in the city of Peacetopia (case study)
  • Autonomous driving (case study)
Programming Assignments (due at 11am):
  • Tensorflow
Midterm Review 10/30 Handouts
Convolutional Neural Networks (Course 4)
Lecture 6 10/31 Advanced Lecture Topic:
  • Deep Learning Project strategy - Case studies
Completed modules:
  • C4M1: Foundations of Convolutional Neural Network
  • C4M2: Deep Convolutional Models
Handouts Quizzes (due at 11am):
  • The basics of ConvNets
  • Convolutional models
Programming Assignments (due at 11am):
  • Convolutional Neural Network - Step by Step
  • Convolutional Neural Network - Application
  • Keras Tutorial: This assignment is optional.
  • Residual Networks
Midterm 11/02
Friday
Midterm Exam
  • Date: November 02, 2018
  • Time: 3pm - 6pm
  • Locations:
    Last names A-K: STLC 111 (Google Maps)
    Last names L-Z: Cubberley Auditorium (Google Maps)
Alternate Midterm 11/05
Monday
Alternate Midterm Exam
  • Date: November 05, 2018
  • Time: 6pm - 9pm
  • Location: 260-113
Lecture 7 11/07 Advanced Lecture Topics:
  • Interpretability of Neural Network
Completed modules:
  • C4M3: ConvNets Applications (1)
  • C4M4: ConvNets Applications (2)
Handouts Optional Reading Quizzes (due at 11am):
  • Detection Algorithms
  • Special Applications: Face Recognition and Neural Style Transfer
Programming Assignments (due at 11am):
  • Car Detection with YOLOv2
  • Art Generation with Neural Style Transfer
  • Face recognition for the Happy House
Project Milestone Due 11/09
Friday 11:59pm
Sequence Models (Course 5)
Lecture 8 11/14 Advanced Lecture Topic:
  • Career Advice
  • Reading Research Papers
Completed modules:
  • C5M1: Recurrent Neural Networks
Handouts Optional Reading Quizzes (due at 11am):
  • Recurrent Neural Networks
Programming Assignments (due at 11am):
  • Building a Recurrent Neural Network - Step by Step
  • Dinosaur Land -- Character-level Language Modeling
  • Jazz improvisation with LSTM
Thanksgiving break (Enjoy!)
Lecture 9 11/28 Advanced Lecture Topics:
  • Deep Reinforcement Learning
Completed modules:
  • C5M2: Natural Language Processing and Word Embeddings
  • C5M3: Sequence-to-Sequence Models
Handouts Optional Reading Quizzes (due at 11am):
  • Natural Language Processing and Word Embeddings
  • Sequence Models and Attention Mechanism
Programming Assignments (due at 11am):
  • Operations on Word Vectors - Debiasing
  • Emojify!
  • Neural Machine Translation with Attention
  • Trigger Word Detection
Lecture 10 12/05 Advanced Lecture Topics:
  • Conversational Assistants
  • Class Wrap-Up
Handouts
Poster Session 12/14
Friday
Poster Session
Final Project Report Due 12/16
Sunday, 11:59pm