Advanced Model Operationalization

This course will teach how you to operationalize your models in a scalable and robust way. You first learned how to put your models behind APIs in our Model Operationalization course, now advance those skills to deploy your APIs into the Cloud! This will enable your models to generate predictions for the whole business at any time, at any scale.

Duration: 2 Days

Star Level: Expert

Certification: Yes


MIacademy / Badge Overview / Open Course Calendar / 4222-Advanced Model Operationalization

Course Description

One of the most critical but often overlooked aspects of the machine learning process is the operationalization of models. Machine learning models have no tangible business benefits until they’re operationalized, and few businesses are prepared to integrate them into the real-life context of operations. This Advanced Model Operationalization course practices the specific steps to removing your AI initiative from the silos and putting it into production at scale. The first day will begin by teaching you how to deploy APIs that use models into the Cloud. Then we will look into serverless deployment, when and why to use it along with the pros and cons. To finish off we will delve into governance and control mechanisms for model operationalization including orchestration, versioning of models and reproducibility of results. The second day will have a strong focus on operationalizing models in Cloud machine learning services like SageMaker, understanding how to leverage this to train, deploy and improve models. The final stretch will push you to combine all this knowledge and design a solution for model operationalization. You will have to compare the different services and deployments methods and consider the business needs and technical requirements to tailor a solution that fits.



Why is this for you?


Being able to build a model is not enough anymore, you also need to be able to bring it into production in a robust way. And moving from the academics of machine learning to the deployment of it is difficult. There’s a wall between the data science and the economics in projects. Months go by with experimenting, building, tweaking, and soon your stakeholders are getting impatient, thinking the final product will never appear. Thus, practicing the tools to operationalize your models is the most crucial skill for achieving impact. The tool this training focuses on, Cloud services, is gaining popularity rapidly to become a leading player with advantages in availability and scalability. Many companies are making the transition to the Cloud and you should be prepared with the knowledge and best practices too.



Who should attend?


The content of this training hits right at the intersection of data science and data engineering. Therefore, this training is perfect for both Data Scientists and Data Engineers who have already completed the pre-requisite badge Model Operationalization (4210).  If you currently feel overwhelmed by all the options and services available for operationalization and are seeking some clarity, this course will be your guide; helping you sort the advantages and disadvantages of each option, so you can make informed decisions and optimize model performance over time.



Learning Goals


    • Deploying APIs – Deploy APIs that use models for inference in the Cloud
    • Serverless deployment – Explain what serverless deployment is and argue its pros and cons
    • Governance and control – Explain and understand the importance of governance and control mechanisms for model operationalization
    • Leveraging Cloud ML – Operationalize models in Cloud machine learning services like SageMaker and understand how to leverage the Cloud for model operationalization
    • Architecting for model operationalization – Design a solution for model operationalization considering business needs and technical requirements



Theory and practical use


Each training in the GAIn portfolio combines high-quality standardized training material with theory sessions from experts and hands-on experience where you directly apply the material to real-life cases. Each training is developed by top of the field practitioners which means they are full of industry examples along with practical challenges and know-how, fueling the interactive discussions during training. We believe this multi-level approach creates the ideal learning environment for participants to thrive.





    • Data
    • Technology
    • Model Operationalization
    • SageMaker
    • Cloud
    • Modeling
    • APIs


Interested in taking the course?

Open Course Schedule


MIacademy does offer part of its portfolio in an Open Course Schedule Format in our location in the center of Amsterdam. Via the form below you can register your interest to participate. Our team will contact you to finalize the booking and answer any questions you may have.

All of our courses are delivered by our expert trainers.


If no dates are mentioned. The specific course is not scheduled yet in 2020. If this is the case you can use the form to register your interest. In case there is enough demand MIacademy can schedule additional courses and will notify you.

Dates & Availability


In-company Training Programs

Are you are interested to train a larger group of people, looking for specific training pe or and/or interested in creating a company-wide program? We will be happy to assist!

Whether you have a very specific training need (for example: training your Data Engineers on advanced technical topics, or your Data Scientists on model implementation), or the need for a large transformational program, or something in between, we can help. Over the past 13 years, we have built up extensive experience not only in the implementation of multi-year, multi-population, multi-country programs but also in providing high quality, very specific modules for specific target groups. Both in in-house set-ups and cross-company programs. Not sure what type of program would fit your organization best? We’d be happy to discuss the best approach together.