Complete online at your own pace (Self-paced)
We have partnered with AWS training and certification to provide a curated learning journey to develop your understanding and skills in AI and Machine Learning. You can access the online modules at your own pace and on-demand. You will need an Amazon account to access the material which you can sign up to for free.
Modules included in this pathway are:
Demystifying AI/ML/DL (45 minutes)
After taking this set of courses, you’ll understand how artificial intelligence (AI) led to machine learning (ML), which then led to deep learning (DL).
Exploring the Machine Learning Toolset (2.5 hours)
No matter what your background or experience, you can use machine learning. In this course, we’ll show you some of the AWS machine learning services you can use to build models and add intelligence to applications.
Developing Machine Learning Applications (2 hours)
In this curriculum, you’ll explore Amazon’s fully managed ML platform, Amazon SageMaker. Specifically, we’ll discuss how to train and tune models, how certain algorithms are built in, how you can bring your own algorithm, and how to build for particular use cases like recommender systems or anomaly detection.
Machine Learning Terminology and Process (1 hour)
This course introduces you to basic machine learning concepts and the machine process the data goes through. We explore each step in the machine learning process in detail and explain some of the common terms and techniques that occur during a phase of a ML project.
Machine Learning for Business Challenges (1 hour)
Machine learning (ML) can help you solve business problems in ways that weren’t possible before—but you’ve got to think big. Listen in as some of Amazon’s own Machine Learning Scientists discuss how to make the most of ML. We’ll cover ML terminology, business problems, use cases, and examples. By the end of this course, you’ll have a better understanding of how to think about machine learning business challenges and decisions.
ML Building Blocks: Services and Terminology (1 hour)
These two courses clarify both the machine learning stack and the terms and processes that will help you build a good foundation in machine learning. You’ll explore the AWS ML stack through application use cases, platform services, frameworks, interfaces, and infrastructure. You’ll also learn how a business problem becomes a machine learning problem, and how data is moved and processed throughout the pipeline to train models and create predictions.
Twitch Series: AWS Power Hour Machine Learning (8 hours)
This course is a series of seven modules from the Twitch Series: AWS Power Hour Machine Learning (ML). Each module features the AWS hosts and a special guest as they demonstrate how to build apps with artificial intelligence (AI) Services from AWS. Designed for developers without prior ML experience, the course helps you learn to build apps that showcase natural language, speech recognition, and other personalized recommendations. The course provides in-depth technical education in a fun and engaging environment.