Machine Learning (ML) is one of the fastest-growing areas of technology and a highly in-demand skill in today’s job market; hence, the need to get the AWS machine learning certification as an upgrade.
The World Economic Forum states that artificial intelligence (AI) growth could add 58 million net new jobs over the next few years, but it is estimated that there are currently 300,000 AI engineers worldwide, but millions are needed.
This means you have a unique and immediate opportunity to start learning the essential ML concepts used to build AI applications – whatever your skill level.
By learning the fundamentals of ML now, you can keep up with that growth, expand your skills and even advance your career.
In this course, you will learn how to get started with AWS Machine Learning. Key topics include Machine Learning on AWS, Computer Vision on AWS, and Natural Language Processing (NLP) on AWS.
Each topic consists of multiple modules that dive deep into a variety of ML concepts, AWS services, and expert insights into how to put the concepts into practice.
Table of Contents
- What is AWS Machine Learning?
- What does the AWS Machine Learning test do?
- How much does the AWS Machine Learning exam cost?
- What Experience Do You Need for the AWS Machine Learning?
- Who should participate in AWS Machine Learning?
- Is AWS Machine Learning worth it for data scientists?
- Is AWS Machine Learning worth it for developers?
- Is AWS Machine Learning worth it for a data analyst?
- Is AWS machine learning worth it?
- Using AWS Machine Learning to learn skills
- Using AWS Machine Learning to Validate Skills
- What are the different AWS machine learning certifications?
- Why should you learn AWS?
- Editor’s Recommendations
What is AWS Machine Learning?
The AWS Machine Learning Certification is a specialty-level qualification from AWS that covers implementing machine learning solutions over AWS to solve business problems.
The AWS Machine Learning Certification covers both machine learning in general and AWS in particular. The content is about the implementation of machine learning approaches and solutions via the AWS cloud and services.
The specialty-level designation means it falls outside of the three-tier structure that AWS uses to categorize most of its certifications: Foundational, Associate, and Professional.
It is a highly specialized and challenging certification exam with no formal requirements.
Earning the AWS Machine Learning certification means that an individual not only has a solid understanding of the fundamentals of machine learning but also knows how to transform those fundamentals into usable solutions via the AWS cloud.
In other words, being an AWS cloud services expert is not enough to earn the AWS Machine Learning, but neither is being an expert in machine learning solutions without AWS experience.
While the ML – Specialty certification is difficult, it is definitely doable, even without the recommended years of experience.
If you come from any data science background, I encourage you to look at this certification or at least get acquainted with what AWS has to offer to help you scale your projects.
In order to earn AWS Machine Learning certification, one exam must be passed: the MLS-C01, which can be taken online.
What does the AWS Machine Learning test do?
The MLS-C01 is the only exam required to earn AWS Machine Learning Certification. It is a 180-minute exam with 65 questions. The questions are multiple-choice and multiple responses.
Multiple-choice questions have only one correct answer, while multiple response questions have two or more correct answers from five or more options. There are four main sections or “domains” of the exam:
- Area 1: Data Engineering
- Area 2: Exploratory data analysis
- Area 3: Modelling
- Area 4: Implementation and operation of machine learning
Although highly technical and focused on machine learning algorithms and processes, AWS emphasizes that someone with an AWS Machine Learning certificate knows how to choose the right machine learning approach to a business problem and the right AWS service to implement it.
How much does the AWS Machine Learning exam cost?
The AWS Machine Learning MLS-C01 certification exam costs $300. Because it is such a specialized and challenging exam, you will definitely want to take additional training and courses.
Although the test costs only $300, don’t count that as the total cost of earning the AWS Machine Learning certificate.
Add in the price of the courses you’re taking—and the likely months of preparation time—to give you a better sense of the total cost.
What Experience Do You Need for the AWS Machine Learning?
AWS recommends 1-2 years of machine learning and deep learning experience before taking the AWS Machine Learning exam.
You would be best served if this experience was intense and hands-on, rather than being limited to one or two repetitive ML-related tasks.
If you plan to try AWS Machine Learning, you need experience developing and running workloads for machine learning and deep learning solutions.
And specifically, you want to see these workloads run on AWS.
As we mentioned earlier, the AWS Machine Learning exam is equal parts specific to AWS and machine learning in general – to that end, you should not only understand how AWS cloud services manage machine learning workloads, but also convenience and Familiarity with machine learning algorithms broad.
The more familiar you are with the intuition behind the decisions machine learning services make and with methods for fundamental hyperparameter tuning, the better prepared you will be for the MLS-C01.
You should have experience with machine learning frameworks, you should be able to follow model training solutions, and you should understand best practices for machine learning deployment and operations.
Who should participate in AWS Machine Learning?
The AWS Machine Learning Certification is ideal for experienced data analysts and machine learning developers.
If your day-to-day work brings you up against business problems that could be solved with the right application of uniquely designed, implemented, and deployed machine learning solutions, AWS Machine Learning is the certification created to solve those problems with the best solutions to match.
Is AWS Machine Learning worth it for data scientists?
Yes, if you work in data science, the AWS Machine Learning certification is definitely worth it. Maybe data science isn’t your current career, but it’s a goal for you. If that’s the case, you should definitely consider this certificate as well.
Data science is not about collecting and archiving data, data science is the art of extracting meaningful insights from vast pools of data.
Machine learning, deep learning, and artificial intelligence offer technical solutions to sift through raw data find the most interesting information, and turn it into useful results.
For data scientists, it looks great on a resume to earn a qualification that certifies you as an expert in implementing machine learning workloads.
The machine learning skills and AWS familiarity you gain will also speed up every part of your job.
Is AWS Machine Learning worth it for developers?
Yes! If you’re building for technology or language that leverages big data sets, consider the AWS Machine Learning Certification.
Especially if you work directly with software and application development, need access to massive amounts of data before developing a custom solution, or use machine learning algorithms to drive your results, the AWS Machine Learning certificate is a great investment.
A key pillar of the AWS Machine Learning certification is its emphasis on selecting the right models for specific machine learning problems or developing solutions that fit business problems.
Employers and managers respect the critical thinking aspect of the certification exam because it empowers you to think using the AI and ML tools at your disposal to provide solutions that save time and effort while delivering high-quality results.
Is AWS Machine Learning worth it for a data analyst?
AWS Machine Learning might be worthwhile for a data analyst, but only if you plan to advance your career into some of the more technical aspects of the job, or if you have the time and energy to master all elements of machine learning algorithms.
For some data analysts, the information in certain parts of the exam may be worth more than the certificate itself.
It might make more sense for them to take a course that prepares students for the exam and skip parts that are overly technical or unrelated to your job, rather than attempting a test as specialized as AWS Machine Learning to pass.
Is AWS machine learning worth it?
AWS Machine Learning is definitely worth it. It is a challenging and specialized qualification that demonstrates a technical professional’s knowledge of some of the most advanced aspects of designing machine learning solutions and implementing them with AWS.
If you are absolutely certain that you will never use AWS in your machine learning career, you might want to consider another machine learning certification.
Otherwise, AWS Machine Learning is a worthwhile investment if you know you’re going to delve deeply into big data, AI, and machine learning.
Using AWS Machine Learning to learn skills
The AWS Machine Learning certification exam is difficult. Even among highly experienced data scientists and machine learning developers, few people can take the exam unprepared.
It is also a young field that is constantly evolving. For this reason, preparing for the AWS Machine Learning exam is a great way to learn machine learning and artificial intelligence skills.
For some people, taking courses designed to help pass the AWS Machine Learning exam is enough.
The exam itself is challenging, and just going through the exam objectives and choosing which elements of data engineering, exploratory analysis, modeling, and implementation you want to use in your own career could be a path to learning the required machine learning skills.
Using AWS Machine Learning to Validate Skills
If you are able to pass the AWS Machine Learning, earning and displaying it on your resume represents deep technical knowledge and critical thinking skills.
Employers and managers understand that it represents a deep familiarity with machine learning algorithms, frameworks, best practices, and the ability to convert all of that knowledge into real-world solutions on AWS.
What are the different AWS machine learning certifications?
Deep knowledge of AWS and SageMaker isn’t enough to pass this exam—you also need a solid understanding of machine learning and the nuances of feature engineering and model optimization that isn’t generally taught in books or classrooms. You just can’t prepare enough for that.
This certification prep course is taught by Frank Kane, who spent nine years working in machine learning at Amazon.
Frank passed this test the first time and knows exactly what it takes for you to pass it yourself. Joining Frank on this course is Stephane Maarek, an AWS Expert and popular AWS Certification teacher on Udemy.
In addition to the 10-hour video course, a 30-minute quick assessment practice exam is included, consisting of the same topics and style as the real exam.
You’ll also get four hands-on labs where you can apply what you’ve learned and gain valuable experience in model optimization, feature engineering, and data engineering.
The AWS Certified Machine Learning Specialty certification is for developers and data scientists who want to validate their machine learning skills on the AWS platform.
The courses in this path teach you how to define a business problem as a machine learning problem, and then how to design, build, deploy, and maintain machine learning solutions on the AWS platform.
These topics are designed to prepare you for the AWS Certified Machine Learning Specialty certification exam.
Specifically, the exam tests a candidate’s ability to design, build, deploy, and maintain machine learning solutions.
This path covers the four major test domains: data engineering, exploratory data analysis, modeling, and machine learning implementation and operations.
The information and resources included in this trial are critical to preparing for the AWS Certified Machine Learning Specialty exam.
A Cloud Guru WS Certified Machine Learning — Specialty 2020-15 hours, 1 practice test
The AWS Certified Machine Learning Specialty 2020 Video Training prepares you for the AWS Certified Machine Learning Specialty exam with some great materials and hands-on exercises.
In this course you will learn:
- The knowledge domains for the AWS Certified Machine Learning Specialty exam
- Best practices for using AWS tools and platforms for data engineering, data analysis, machine learning modeling, model validation, and deployment
- Hands-on labs designed to challenge your intuition, creativity, and knowledge of the AWS platform
With this course, you’ll gain a solid understanding of the services and platforms available on AWS for machine learning projects, build a foundation to pass the certification exam, and feel empowered to use the AWS ML portfolio in your own use in real applications.
The AWS Certified Database Specialty certification is a very challenging certification for AWS. It’s great for assessing your understanding of AWS databases and their integrations and troubleshooting.
We want to help YOU pass the AWS Certified Database Specialty certification with flying colors.
This AWS Certified Database Specialty course is the first comprehensive course on this new AWS certification.
- It covers in detail all topics of the AWS Certified Database Specialty DBS-C01 exam
- It’s packed with hands-on knowledge of using AWS databases internally and externally
- We will learn by doing something
- It teaches you how to prepare for the AWS exam
- It’s fast-paced and to the point
- All 550+ slides available as a downloadable PDF file
The course is designed for beginning developers and data scientists who want to gain a basic understanding of AWS SageMaker and solve challenging real-world problems.
Basic knowledge of machine learning, Python programming and AWS cloud is recommended.
Several videos are available on YouTube that thoroughly explain the basic concepts of ML and guide viewers through the entire ML lifecycle, showing how to use Amazon SageMaker, Jupyter notebooks, and more.
Videos like this might be helpful for those who may not be as hands-on as they would like. You can also get a better feel for the user experience and UI that ML engineers and data scientists use.
Why should you learn AWS?
1) AWS – fastest-growing public cloud in the world
AWS was officially launched in 2006 and by 2007 there were around 180,000 developers on the platform. By 2015, AWS revenue was $6 billion per year, and since then revenue has doubled and grown exponentially.
AWS enjoys the benefit of a 7-year head start before facing like-minded competition, and since then the team has never let up. AWS continues to increase its growth every quarter.
2) AWS Skills on Most In-Demand Skills list since 2015
Knowing which way the wind is blowing and then keeping up with the change in the same direction is the order of the day. And as of today, the wind seems to be blowing into the AWS cloud.
As Google trends show, companies around AWS are heading for a serious skills shortage. Professionals who long for a lucrative career should head in this direction.
With more than 350,000 professionals needing to fill cloud job roles, there is clearly a huge opportunity for people who can demonstrate their skills. AWS skills top the list of most in-demand skills for employers.
3) Increased enterprise cloud migration to AWS
Not only small organizations are migrating to the cloud, retail companies are also migrating to the cloud at a rapid pace.
Organizations migrating their services and applications to the cloud face numerous challenges and obstacles. The cloud platforms like AWS, Azure, Google offer several automated functions but migration is not one of them.
This means businesses depend on bespoke, professional services from vendors. There is an increasing demand for cloud experts who can manage migration projects securely and in an organized manner.
This requires professionals to have in-depth knowledge of the chosen cloud platform such as AWS. Becoming a Certified AWS Solutions Architect equips you with the entire process of moving from an existing on-premises application to an AWS cloud.
4) AWS careers pay top money
AWS Certified Solutions Architects – Associate Professionals earn an average salary of $121,292, over $13,000 more than the average salary of the top 15 IT certified professionals.
Salaries for AWS skills in premium areas like Austin, San Francisco, Washington, or Boston are 25% higher than usual.
According to PayScale, non-architect AWS cloud jobs fetch comparatively lower paychecks than architect jobs. The highest-paying positions that can help professionals make the most money from their cloud jobs are –
- AWS Enterprise Cloud Architect – $138,051
- AWS Senior Cloud Solutions Architect – $132,092
5) Affordable pricing and access to Learning AWS Free Tier
Professionals who are new and want to get hands-on experience with the technology can create an AWS account and access the free tier provided by AWS for one year.
Popular free AWS services include -Amazon RDS, Elastic Load Balancing, EC2, S3. Each service has a certain usage limit without incurring any fees.
This is enough for people starting to learn AWS. However, AWS offers a flexible pay-as-you-use approach, and novices can consume these services based on hours and storage usage as needed.
So if you’re really serious and committed to learning AWS, we recommend you at least take a look at Learning Infrastructure as Code. It doesn’t take as much effort as regular application coding, it could save you a lot of headaches, and it might just be the benefit you need to get the job you want.
However, if you’re just starting out, don’t feel bad if you’re just using the UI to build infrastructure within AWS, just know that there are better ways to work with AWS and create a plan around them Ideas to consider in the future.