Syllabus and Course Schedule

Time and Location: Monday 11:30-12:50pm, Hewlett 102

EventDateDescriptionMaterials and Assignments
Lecture 1 9/25 Introduction
  1. The AI world
  2. Logistics of the course
  3. Presentation of the Syllabus
Handouts
Lecture 2 10/02 Advanced Lecture: The mathematics of backpropagation

Completed modules
  • C1M1: Introduction to deep learning
  • C1M2: Neural Network Basics
Quizzes (due at 9am):
  • Introduction to deep learning
  • Neural Networks Basics
Programming Assignments (due at 9am):
  • Python Basics with Numpy (Optional)
  • Logistic Regression with a neural network mindset
Handouts
Lecture 3 10/09 Advanced Lecture: Overview of various deep learning topics

Completed modules
  • C1M3: Shallow Neural Network
  • C1M4: Deep Neural Networks
Quizzes (due at 9am):
  • Shallow Neural Networks
  • Key concepts on Deep Neural Networks
Programming Assignments (due at 9am):
  • Planar data classification with a hidden layer
  • Building your Deep Neural Network: step by step
  • Deep Neural Network - Application
Handouts
Lecture 4 10/16 Advanced Lecture: Mathematics behind Regularization and Initialization

Completed modules
  • C2M1: Practical aspects of deep learning
Quizzes (due at 9am):
  • Practical aspects of deep learning
Programming Assignments (due at 9am):
  • Initialization
  • Regularization
  • Gradient Checking
Project Proposal (due at 11:59pm): [form]
Lecture 5 10/23 Advanced Lecture: Advanced topics in Object Detection

Completed modules
  • C2M2: Optimization Algorithm
  • C2M3: Hyperparameter tuning, Batch Normalization, Programming Frameworks
Quizzes (due at 9am):
  • Optimization Algorithm
  • Hyperparameter tuning, Batch Normalization, Programming Frameworks
Programming Assignments (due at 9am):
  • Optimization
  • Tensorflow
Handouts
Lecture 6 10/30 Advanced Lecture: Deep Reinforcement Learning

Completed modules
  • C3M1: ML Strategy (1)
  • C3M2: ML Strategy (2)
Quizzes (due at 9am):
  • Bird recognition in the city of Peacetopia (case study)
  • Autonomous driving (case study)
Handouts
Lecture 7 11/06 Advanced Lecture: Overview of Recurrent Neural Network

Completed modules
  • C4M1: Foundations of Convolutional Neural Network
  • C4M2: Deep Convolutional Models
Quizzes (due at 9am +1 extra day offered):
  • The basics of ConvNets
  • Convolutional models
Programming Assignments (due at 9am +1 extra day offered):
  • Convolutional Neural Network - Step by Step
  • Convolutional Neural Network - Application
  • Keras Tutorial
  • Residual Networks
Lecture 8 11/13 Advanced Lecture: Attention models

Completed modules
  • C4M3: ConvNets Applications (1)
  • C4M4: ConvNets Applications (2)
Quizzes (due at 9am):
  • Detection algorithms
  • Special applications
Programming Assignments (due at 9am):
  • Car Detection with YOLOv2
  • Art generation with Neural Style Transfer
  • Face Recognition for the Happy House
Handouts
Thanksgiving break 11/17 Project Week Project Milestone (due at 11:59pm): [more info]
Lecture 9 11/27 Guest lecture: AI for healthcare, Pranav Rajpurkar

Lecture 10 12/04 Advance Lecture BLUE score, Beam Search and Speech Recognition with CTC loss

Completed modules
  • C5M1: Recurrent Neural Networks
  • C5M2: Natural Language Processing and Word Embeddings
Programming Assignments (due at Tuesday 12/05 5pm):
  • Building a Recurrent Neural Network - Step by Step
  • Operations on Word Vectors - Debiasing
Handouts
Final Presentations 12/11 Hewlett102, 8:30-11:30am Monday 12/11
Final Project 12/12 Readings Submit Final Project (due at 11:59pm, no late day): [more info]

Programming Assignments (due at Tuesday 12/12 11:59pm):
  • Emojify