Machine Learning (Certificate)
11 week course taught by Andrew Ng, Adjunct Professor of Computer Science at Stanford University.
Course delivered by Stanford University on Coursera.
Syllabus (click to expand)
Linear Regression
Logistic Regression
Regularization
Neural Networks: Representation
Neural Networks: Learning
Advice for Applying Machine Learning
Machine Learning System Design
Support Vector Machines
Unsupervised Learning
Dimensionality Reduction
Anomaly Detection
Recommender Systems
Large Scale Machine Learning
Application Example: Photo OCR
Probabilistic Graphical Models (Certificate)
4 week course taught by Daphne Koller, professor at Stanford University.
Course delivered by Stanford University on Coursera.
Syllabus (click to expand)
Bayesian Network (Directed Models)
Template Models for Bayesian Networks
Structured CPDs for Bayesian Networks
Markov Networks (Undirected Models)
Decision Making
Knowledge Engineering
Deep Learning Specialization (Certificate)
Series of 5 courses taught by Andrew Ng, Adjunct Professor of Computer Science at Stanford University.
Courses delivered by deeplearning.ai on Coursera.
Neural Networks and Deep Learning (Certificate)
Syllabus (click to expand)
Introduction to Deep Learning
Neural Networks Basics
Shallow Neural Networks
Deep Neural Networks
Improving Deep Neural Networks (Certificate)
Syllabus (click to expand)
Practical aspects of Deep Learning
Optimization algorithms
Hyperparameter tuning
Batch Normalization
Programming Frameworks
TensorFlow
Structuring Machine Learning Projects (Certificate)
Syllabus (click to expand)
Error diagnostics
Promising directions for error reduction
Mismatched Training/Test sets
Comparing/surpassing human-level performance
End-to-end learning
Transfer learning
Multi-task learning
Convolutional Neural Networks (Certificate)
Syllabus (click to expand)
Foundations of Convolutional Neural Networks
Deep convolutional models
Residual Networks
Detection algorithms
Car detection with YOLO
Art generation with Neural Style Transfer
Face Recognition
Sequence Models (Certificate)
Syllabus (click to expand)
Recurrent Neural Networks
Character-Level Language Modeling
Long Short-Term Memory
Natural Language Processing
Word Embeddings
Attention mechanism
Neural Machine Translation
Trigger word detection
TensorFlow in Practice Specialization (Certificate)
Series of 4 courses taught by Laurence Moroney, Artificial Intelligence Advocate at Google Brain.
Courses delivered by deeplearning.ai on Coursera.
Introduction to TensorFlow for Artificial Intelligence, Machine Learning and Deep Learning (Certificate)
Syllabus (click to expand)
TensorFlow, Python and Google Colaboratory
Computer Vision in TensorFlow
Enhancing Vision with CNNs
Real-world image classification
Convolutional Neural Networks in TensorFlow (Certificate)
Syllabus (click to expand)
Exploring larger datasets
Image augmentation
Transfer Learning
Multiclass classification
Natural Language Processing in TensorFlow (Certificate)
Syllabus (click to expand)
Word based encodings
Subwords text encoding
Tokenization
Word embeddings
Sequence models
LSTMs
Word-based RNN text generation
Character-based RNN text generation
Sequences, Time Series and Prediction (Certificate)
Syllabus (click to expand)
Evaluation metrics
Forecasting
Data synthesis
DNNs for Time Series
RNNs for Time Series
Time Series convolutions
Bi-directional LSTMs
TensorFlow: Data and Deployment Specialization (Certificate)
Series of 4 courses taught by Laurence Moroney, Artificial Intelligence Advocate at Google Brain.
Courses delivered by deeplearning.ai on Coursera.
Browser-based Models with TensorFlow.js (Certificate)
Syllabus (click to expand)
Introduction to TensorFlow.js
Image Classification in the browser
Converting models to TensorFlow.js
Transfer Learning with Pre-Trained Models
Device-based Models with TensorFlow Lite (Certificate)
Syllabus (click to expand)
TensorFlow Lite components & architecture
Persistence, performance and optimizations
Model conversion and Transfer Learning
Building TF models on Andriod
Building TF models on iOS
Building TF models on embedded systems
Data Pipelines with TensorFlow Data Services (Certificate)
Syllabus (click to expand)
Introduction to TFDS
Data input pipelines
Feature Column API
Data transformations
Data loading
Parallelism APIs
Publishing datasets
Advanced Deployment Scenarios with TensorFlow (Certificate)
Syllabus (click to expand)
Deployment using TFX
TensorFlow Serving
TensorFlow Hub
Transfer learning using TF Hub
Federated Learning