How hard is the AWS Machine Learning specialty?

There is a huge demand for skilled professionals in the Machine Learning domain, and the AWS Machine Learning – Specialty Certification is highly sought after by aspiring professionals for an edge in the job market. However, the certification is not considered the easiest to achieve, with plenty of challenging aspects and prerequisites that one needs to keep in mind. Let us take a look at what the certification is all about and whether there is a prompt solution to make achieving it an easier task.

AWS Machine Learning – Specialty Certification – An Overview

The AWS Machine Learning – Specialty Certification validates the expertise of an individual in working with ML models, concerning their building, training, and deployment on the AWS Cloud platform. It is meant for individuals performing development or data science roles with at least one year of experience in ML or deep learning workloads on AWS. This certification validates the ability to express intuition behind basic ML algorithms, conduct hyperparameter optimization, and follow best practices in model training, deployment, and operations. To achieve this certification, candidates must pass the AWS Certified Machine Learning – Specialty exam (MLS-C01).

What Aspects of the AWS Machine Learning – Specialty Certification are Challenging?

The AWS Machine Learning – Specialty is an industry-reputed certification which is in high demand among ML aspirants who wish to have a badge of expertise associated with them to open a number of employment opportunities among a host of other reasons. The certification, albeit not hard, does have a few challenges at hand which one should know prior to taking it up. 

The first challenge is the various prerequisites on needs to have beforehand, which include: –

• At least two years of hands-on experience in developing, architecting, and running ML or deep learning workloads in the AWS Cloud.
• Ability to express the intuition behind basic ML algorithms.
• Experience performing basic hyperparameter optimization.
• Familiarity with ML and deep learning frameworks.
• Proficiency in following model-training, deployment, and operational best practices.

For candidates who may not have a few of the prerequisites fulfilled, the curriculum for the AWS Certified Machine Learning – Specialty exam (MLS-C01) may have a few concepts that might be tough to grasp. These concepts are mentioned as follows: –

• Data Engineering
• Exploratory Data Analysis 
• Modeling
• Machine Learning Implementation and Operations 

Take a detailed look at the certification. Check out more information here.

How Can Cloud Wizard Help Simplify The Path to Certification?

There is no challenge in achieving the AWS Machine Learning – Specialty Certification which cannot be dealt with. All you need is to have an authorized training partner to help you navigate through the various topics that encompass the certification exam well in advance so that you gain confidence in your ML knowledge and skills. An Advanced Tier Training partner like Cloud Wizard can be of great help here.

Cloud Wizard’s training platform offers a structured approach to learning, with classroom training sessions, special exam prep courses, and hands-on labs to make the challenges faced in the exam feel less intimidating. Experienced instructors provide valuable insights and strategies to navigate the exam domains effectively. By partnering with Cloud Wizard, you gain not just proficiency in AWS ML concepts, but also take a few steps closer to being a certified ML professional!

Want to explore further? Consider taking a look at a host of other AWS certifications here!