EdX

Introduction to Machine Learning on AWS (edX)

Offered by AWS,
Introduction to Machine Learning on AWS (edX)

This course is intended for software developers and engineers taking their first steps with the AWS services that do much of heavy lifting of Machine Learning for you. In this course, we start with some services where the training model and raw inference is handled for you by Amazon. We'll cover services which do the heavy lifting of computer vision, data extraction and analysis, language processing, speech recognition, translation, ML model training and virtual agents.

Class Deals by MOOC List - Click here and see EdX's Active Discounts, Deals, and Promo Codes.

You'll think of your current solutions and see where you can improve these solutions using AI, ML or Deep Learning. All of these solutions can work with your current applications to make some improvements in your user experience or the business needs of your application.

What you'll learn
At the end of this course, students will be able to:

  • Apply machine learning and artificial intelligence to tasks that you'd normally think you'd need a human to do
  • Understand the differences between Machine Learning, Artificial Intelligence and Deep Learning
  • Analyze labels and images using advanced technology
  • Learn how to host your own machine learning models with Amazon Sagemaker

Syllabus

Week 1:
Video :Course Introduction
Video : Week 1 Introduction
Video : Computer Vision: Amazon Rekognition
Video : Exercise Introduction: Amazon Rekognition
Exercise : Amazon Rekognition
Video : Exercise Walkthrough: Amazon Rekognition
Video : Data extraction and analysis: Amazon Textract
Video : Exercise Introduction: Amazon Textract
Exercise: Amazon Textract
Video : Exercise Walkthrough: Amazon Textract
Video : Language Processing: Amazon Comprehend
Video : Exercise Introduction: Amazon Comprehend
Exercise : Amazon Comprehend
Video : Exercise Walkthrough: Amazon Comprehend
Quiz : Week 1 Quiz

Week 2:
Video : Week 2 Introduction
Video : Speech Recognition: Amazon Transcribe
Video: Language Translation: Amazon Translate
Video: Exercise Introduction: Amazon Transcribe and Amazon Translate
Exercise: Amazon Transcribe and Amazon Translate
Video: Exercise Walkthrough: Amazon Transcribe and Amazon Translate
Video: Virtual Agents: Amazon Lex
Video: Exercise Introduction: Amazon Lex
Exercise: Amazon Lex
Video: Exercise Walkthrough: Amazon Lex
Video: Amazon SageMaker
Video: Demo: Amazon SageMaker
Quiz: Week 2 Quiz

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Introduction to Bayesian Statistics Using R (edX) EdX
University of Canterbury,UCx

Introduction to Bayesian Statistics Using R (edX)

Learn the fundamentals of Bayesian approach to data analysis, and practice answering real life questions using R. Basics of Bayesian Data Analysis Using R is part one of the Bayesian Data Analysis in R professional certificate. Bayesian approach is becoming increasingly popular in all fields of data analysis, including but not limited to epidemiology, ecology, economics, and political sciences. It also plays an increasingly important role in data mining and deep learning. Let this course be your first step into Bayesian statistics.

Self Paced
Self-Paced
Recommender Systems: Behind the Screen (edX) EdX
Université de Montréal,UMontrealX

Recommender Systems: Behind the Screen (edX)

How are items recommended when you’re browsing for movies, jobs or clothing online? Register here and you’ll discover the fundamental concepts and methods allowing the most relevant item suggestions to users from e-commerce to online advertisement. In this course, you will explore and learn the best methods and practices in recommender systems, which are an essential component of the online ecosystem. This course was developed by IVADO and HEC Montréal as part of a workshop that took place in Montreal.

Self Paced
5-12 Weeks
PyTorch Basics for Machine Learning (edX) EdX
IBM

PyTorch Basics for Machine Learning (edX)

This course is the first part in a two part course and will teach you the fundamentals of PyTorch. In this course you will implement classic machine learning algorithms, focusing on how PyTorch creates and optimizes models. You will quickly iterate through different aspects of PyTorch giving you strong foundations and all the prerequisites you need before you build deep learning models.

Self Paced
Self-Paced
Deep Learning through Transformative Pedagogy (edX) EdX
University of Queensland,Microsoft,UQx

Deep Learning through Transformative Pedagogy (edX)

How can powerful teaching strategies and effective learning activities enhance deep learning? This education course has been developed for educators and education leaders. It explores deep learning by bringing together the most up-to-date research from cognitive psychology, contemporary educational theories, and neuro-scientific perspectives.

Self Paced
4 Weeks
Essentials of Genomics and Biomedical Informatics (edX) EdX
IsraelX

Essentials of Genomics and Biomedical Informatics (edX)

This course presents clinicians and digital health enthusiasts with an overview of the data revolution in medicine and how to exploit it for research and in the clinic. The course will not make you a bioinformatician but will introduce the main concepts, tools, algorithms, and databases in this field.

Self Paced
5-12 Weeks
High-Dimensional Data Analysis (edX) EdX
HarvardX,Harvard University

High-Dimensional Data Analysis (edX)

A focus on several techniques that are widely used in the analysis of high-dimensional data. If you’re interested in data analysis and interpretation, then this is the data science course for you. We start by learning the mathematical definition of distance and use this to motivate the use of the singular value decomposition (SVD) for dimension reduction and multi-dimensional scaling and its connection to principle component analysis.

Self Paced
Self-Paced
Data Science: Capstone (edX) EdX
HarvardX,Harvard University

Data Science: Capstone (edX)

Show what you’ve learned from the Professional Certificate Program in Data Science. To become an expert data scientist you need practice and experience. By completing this capstone project you will get an opportunity to apply the knowledge and skills in R data analysis that you have gained throughout the series. This final project will test your skills in data visualization, probability, inference and modeling, data wrangling, data organization, regression, and machine learning.

Self Paced
Self-Paced
Advanced Bayesian Statistics Using R (edX) EdX
University of Canterbury,UCx

Advanced Bayesian Statistics Using R (edX)

Now that you know the basics of Bayesian inference, dive deeper to explore its richness and flexibility more fully. Let’s take a closer look at modeling latent variables, Bayesian model averaging, generalised linear models, and MCMC methods. Advanced Bayesian Data Analysis Using R is part two of the Bayesian Data Analysis in R professional certificate.

Self Paced
Self-Paced
CS50's Introduction to Artificial Intelligence with Python (edX) EdX
HarvardX,Harvard University

CS50's Introduction to Artificial Intelligence with Python (edX)

Learn to use machine learning in Python in this introductory course on artificial intelligence. AI is transforming how we live, work, and play. By enabling new technologies like self-driving cars and recommendation systems or improving old ones like medical diagnostics and search engines, the demand for expertise in AI and machine learning is growing rapidly. This course will enable you to take the first step toward solving important real-world problems and future-proofing your career.

Self Paced
Self-Paced