Type
Virtual
Classroom ILT
Skill Level
Available dates
Learning Path
Virtual
Duration
1 Day
TYPE
Virtual
Classroom ILT
LEARNING PATH
SKILL LEVEL
DURATION
AVAILABLE DATES
Introduction
This course builds upon and extends the DevOps methodology prevalent in software development to build, train, and deploy machine learning (ML) models. The course is based on the four-level MLOPs maturity framework. The course focuses on the first three levels, including the initial, repeatable, and reliable levels. The course stresses the importance of data, model, and code to successful ML deployments. It demonstrates the use of tools, automation, processes, and teamwork in addressing the challenges associated with handoffs between data engineers, data scientists, software developers, and operations. The course also discusses the use of tools and processes to monitor and take action when the model prediction in production drifts from agreed-upon key performance indicators.
Audience profile
This course is intended for:
- MLOps engineers who want to productionize and monitor ML models in the AWS cloud
- DevOps engineers who will be responsible for successfully deploying and maintaining ML models in production
Pre-requisites
It is recommended that attendees of this course have:
- Attended AWS Technical Essentials
- DevOps Engineering on AWS, or equivalent experience
- Practical Data Science with Amazon SageMaker, or equivalent experience
Course objectives
This course is designed to teach you how to:
- Explain the benefits of MLOps
- Compare and contrast DevOps and MLOps
- Evaluate the security and governance requirements for an ML use case and describe possible solutions and mitigation strategies
- Set up experimentation environments for MLOps with Amazon SageMaker
- Explain best practices for versioning and maintaining the integrity of ML model assets (data, model, and code)
- Describe three options for creating a full CI/CD pipeline in an ML context
- Recall best practices for implementing automated packaging, testing and deployment. (Data/model/code)
- Demonstrate how to monitor ML based solutions
- Demonstrate how to automate an ML solution that tests, packages, and deploys a model in an automated fashion; detects performance degradation; and re-trains the model on top of newly acquired data
Course content
Session 1: Introduction to MLOps | |
|
|
|
|
Session 2: Initial MLOps: Experimentation Environments in SageMaker Studio | |
|
|
|
|
Session 3: Repeatable MLOps: Repositories | |
|
|
|
|
Session 4: Repeatable MLOps: Orchestration | |
|
|
|
|
|
|
|
|
|
|
Session 5: Reliable MLOps: Scaling and Testing | |
|
|
|
|
|
|
Session 6: Reliable MLOps: Monitoring | |
|
|
|
|
|
|
Associated certifications and exam
The AWS Certified Machine Learning – Specialty (MLS-C01) exam is intended for individuals who perform an artificial intelligence and machine learning (AI/ML) development or data science role. The exam validates a candidate’s ability to design, build, deploy, optimize, train, tune, and maintain ML solutions for given business problems by using the AWS Cloud. The exam also validates a candidate’s ability to complete the following tasks:
- Select and justify the appropriate ML approach for a given business problem
- Identify appropriate AWS services to implement ML solutions
- Design and implement scalable, cost-optimized, reliable, and secure ML solutions
There are two types of questions on the exam:
- Multiple choice: Has one correct response and three incorrect responses (distractors)
- Multiple response: Has two or more correct responses out of five or more response options
Select one or more responses that best complete the statement or answer the question. Distractors, or incorrect answers, are response options that a candidate with incomplete knowledge or skill might choose. Distractors are generally plausible responses that match the content area.
Unanswered questions are scored as incorrect; there is no penalty for guessing. The exam includes 50 questions that affect your score.
Amazon Web Services Overview
Amazon Web Services (AWS) are leaders in cloud computing solutions and provide IT infrastructure in the form of online web services.
Torque IT is the first and only Authorized AWS Training Partner in Africa.
Our authorized AWS training solutions, and associated certifications, develop and validate the technical knowledge and skills that are relevant to individuals and organizations that are considering, implementing and maintaining cloud-based solutions.
Our hands-on AWS training courses are for anyone who wants to gain a deeper level of understanding with regard to cloud computing solutions and AWS. AWS Certifications designate individuals who demonstrate knowledge, skills and proficiency with AWS services. AWS Certification exams validate the technical knowledge and skills necessary for building and maintaining applications and services on the AWS Cloud.
Regardless of your level of experience with cloud computing, and AWS, we have a course for you.