Amazon Web Services has taken the market by storm, offering IT courses that enhance an individual’s skill set and help them evolve into a better version of themselves. If you are looking to specialize in a particular field, then pursuing one or more of the certifications that AWS offers will benefit you.
Becoming an AWS Certified ML Specialist allows machine learning professionals to validate their skills as well as expertise in designing, implementing and maintaining different solutions for machine learning on the AWS Cloud Platform. It also fortifies their development, training, tuning and deployment. It is intended for professionals who occupy a development or data science role.
The following are the areas in which an individual’s ability is validated through this certification:
- Knowledge and understanding of the appropriate Machine Learning approaches that should be selected and justified for a specific business issue.
- Knowledge and understanding of the correct identification of the appropriate services in AWS that should be utilized for deploying Machine Learning Solutions.
- Knowledge and understanding of the correct process of identifying as well as implementing scalable, cost-optimized, reliable, and secure Machine Learning Solutions.
Who Can Apply for the AWS Certified Machine Learning Specialist Credential?
This certification is intended for professionals who have had some experience in designing, implementing and maintaining the Machine Learning Solutions for solving business issues, and may even be experts in this area. The certificate validates your skills and helps you become familiar to hiring managers and professionals in the industry as an expert in machine learning. While this exam is intended to be undertaken by development or data science professionals, it is not mandatory that only these people may opt for this credential. These include:
- Developers
- Business Decision Makers
- Data Scientists
- Data Platform Engineers
- Anybody else interested in pursuing their career in Machine Learning
Recommended Experience and Knowledge
Let’s take a look at the experience and knowledge required before you can enroll in this course. While these are recommendations and not mandatory, it is always better to have them, since it will give you an edge over others.
- 1-2 practical experience of developing, architecting and running machine/ deep learning solutions on the AWS.
- Hands-on experience in performing the basic optimization tasks for hyper-parameter.
- Ability to express the main purpose of the basic algorithms of machine learning.
- In-depth knowledge and understanding of machine learning as well as deep learning frameworks and experience in using them.
- The ability to deploy and follow the best practices for model training, implementation and operations.
AWS Certified Machine Learning Specialist – Beta Exam
The format of the exam is the same as that of the other certification exams offered by AWS: multiple choice as well as multiple answer questions. However, the one advantage you will get by opting to give this exam is that the cost of the exam will be halved to $150, which is a 50% discount on it. The exam is available in only the English language, and as stated previously, consists of only multiple-choice questions.
There is no pre-requisite for enrolling in this course and pursuing the AWS Certified Machine Learning Specialist credential. With the passage of time, the certifications being offered by AWS has become immensely flexible, as it is no longer necessary to have completed the associate or foundational level certifications. However, it is still recommended by experts and veterans to have your basics strong before going ahead with this specialty certification.
The following are the domains which are covered by the exam.
- Data Engineering
- Exploratory data analysis
- Modeling
- Machine Learning Implementation and Operations
20% of the exam tests you on data engineering, whereas, modeling makes up 36% of the exam. Exploratory data analysis comprises 24% of the exam, and machine learning deployment and operations makes up the remaining 20% of the exam. Like all AWS certifications, the AWS Certified Machine Learning Specialist also remains valid for two years, after which you must apply for re-certification. In case the first attempt at the exam is not successful, the candidate receives an exam voucher allowing him or her to retake the full version of the exam without any additional fee.
This was all about the beta exam. Now let’s take a look at the full exam. The full exam is available in two languages: English and Japanese. The cost of the exam is $300. The learnings that are being offered are designed keeping in mind specific roles for machine learning specialists, which include, data scientist, business decision maker, developer and data platform engineer.
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Why Choose AWS Certified Machine Learning Specialist Certification?
There are many different types of machine learning credentials out there, so what makes this one stand out from the crowd? Let’s find out!
- You find out about the latest best practices from cloud-based machine learning
- This course is designed to provide you information and knowledge about useful algorithms
- The techniques are immensely easy to integrate with your applications and offer support for a range of programming languages
- The nature of the AWS cloud is highly elastic, which allows you to handle both small and big data
- You only pay for the skills you wish to gain and no other cost is covered by you
- You will also get to learn about three popular liner algorithms from scratch
Career Outlook
These days, machine learning is said to be one of the most preferred career choices for data and IT Professionals. As more and more companies shift their processes to cloud based systems, the demand for machine learning specialists increases, and those having AWS Certification are bound to reap the benefits. According to a report published by Gartner, AI will create over 2.3 million jobs by 2020. And with each passing day, this number keeps rising. According to the U.S. Emerging Jobs Report published by LinkedIn in 2017, the number of machine learning engineers working in the industry increased by 9.8 times as compared to 2012.
Additionally, in the next couple of years, this number is expected to grow further, with more and more people opting for such jobs as the world advances to a more integrated digital era.
Salary
Most of the candidates appearing for this exam are focused on getting a higher salary after obtaining this credential. That is because AWS certifications lead to high paying jobs, which most people seek. The average salary that can be earned by an individual possessing an AWS certification is $120,000 per year, and this amount can increase depending on the skill set and the specialization of the candidate. According to Glassdoor, the average salary of an AWS Certified Machine Learning Specialist is $142,000 per annum. And this amount can increase as the candidate progresses through his or her career. So, you can be sure to take a handsome salary at home and reap the benefits of the hard work you put in to achieve this certification.
Sample resume of an AWS Certified Machine Learning Specialist
Jon Doe | Your Address | Your contact Details
Objective
To make use of my skills for the betterment of the organization I work for and to provide creative solutions to prevalent as well as new issues.
Experience
ABC Company | 2014 – Present
Software Engineering, Machine Learning
Responsibilities Included;
- Coordinate and work with product managers and data scientists to develop a problem within the business context as well as mathematically.
- Implement validated algorithms within the RBT system and create techniques for visualizing as well as monitoring performance of all the executed algorithms.
- Gained knowledge of developing as well as debugging in Java and C/C++.
- Gained knowledge of more than one machine learning framework.
- Develop prototypes and test them to validate results.
- Assisted in the development, testing and implementation of production solutions.
ABC Corporation | 2011 – 2014
Machine Learning Researcher
Responsibilities Included;
- Coordinate and work closely with the development team in order to ensure the integration of machine learning models is carried out accurately across all platforms.
- Develop new data driven strategies, and gain more insights by developing the team’s capabilities in machine learning and data science.
- Create innovative and unique systematic investment strategies and signals based on research
- Coordinate and work together with the investment team looking after equities, credit, macro, RV, mid-horizon, securitized, etc., with the objective of introducing innovative data sources and cutting-edge techniques across the different funds available.
- Develop results, conduct their analysis and create reports using prototypes as well as proof of concept research projects which focus on new methods, tools, and algorithms, new scientific application or domain areas, and few data sources or sets.
- Create new machine learning models with the objective of detecting any malicious activity on mobile devices.
MPL Corporation
Machine Learning | 2006 – 2010
Responsibilities Included;
- To conduct research and develop new machine learning models for security problems in the areas of application development, networking and data.
- Meet the project’s milestones by providing the production quality code and SW specifications on time.
- Provide the production quality code and SW Specifications in order to engage with the algorithm proliferation activities
- Conduct research and create the deep learning algorithms
- Conduct research and create state of the art methodologies and techniques in the following fields of Machine Learning, Computer Vision and Deep Learning.
- Work with SW, physics, the system and the application group
- In order to monitor and measure the Ad Quality along with its associated user interfaces, work on creating the next generation automation tools.
Education
The University of Johnson and Wales
Bachelor’s in Computer Science | 2002 – 2006
Institute of Computer Science and Technology | 2008 – 2010
Certifications
- AWS Certified Developer
- AWS Certified Solutions Architect
- AWS Certified Machine Learning Specialist
- CompTIA Security +
- CompTIA Cloud +
- Excel in analytical and organizational skills
- Develop data science capability – practical experience of 3 years
- Excellent written as well as oral communication skills
- Proficient in the use of Java, C++, and other coding languages
- Excellent presentation skills
- Ability to read, understand, as well as clearly communicate and explain technical documentation
- Strong technical and business writing skills
- Excel in using SWL, Python, and R. Familiarity with developing and conducting experiments with human subjects
- Experience with working with a financial service organization, in both technical and delivery aspects.
- Exposure to different clients both globally and domestically.
- Have experience of working in different business cultures, with high performing and fast paced teams.
Skills
References
The references will be provided upon request.
Common Interview Questions for an AWS Certified Machine Learning Specialist
Now that you have learned about how to become a machine learning specialist, what it is and what the AWS Certified Machine Learning Specialist credential offers, you need to be aware of what needs to be done after you have cleared the exam and obtained this certification. While the certification is likely to land you in the shortlisted candidates being considered by an organization for the role, how well you do in the interview is what determines whether or not you land the job. Therefore, it is crucial to be prepared for the exam and at the same time be ready to impress not only the hiring manager, but all those who may be present during the interview. So, what can you expect? Let’s find out.
Usually interviewers tend to begin with generic questions that are mostly aimed at getting to know you. Once they are done with those, then they funnel the questions down to the more technical aspects of the jobs, which basically test your skills and knowledge about the subject matter. Here is a basic flow which most of the hiring managers follow.
- Please tell us about yourself.
- Tell us something that is not mentioned in your CV/ resume.
- What do you usually do in your free time?
- Why do you want to switch from your current job?
- What are your career aspirations?
- Where do you see yourself after five years?
- What, according to you, are your strengths and weaknesses?
- Are you currently planning on enhancing your skill set? If yes, then how?
- Have you ever been in a situation where you had to resolve a team conflict? What did you do to resolve it?
- How would you overcome cultural barriers?
Now these questions will give you a general idea of what type of questions to expect at the beginning of the interview and then be prepared for them. After this, the interviewer or hiring manager is likely to move on to the technical questions which test your knowledge of machine learning and exhibit your skills. The following questions will give you a general idea of what type of technical questions to expect.
- You have worked in the industry yourself. Given your experience, please explain machine learning in industry standards.
- You say that you have worked with different algorithms in your CV. What are the different techniques of algorithms in Machine learning?
- Is there is a difference between supervised and unsupervised machine learning?
- Do you know what are the pros and cons of Naïve Bayes?
- Have you ever experienced an instance where there was overfitting in machine learning? What did you do about it?
- According to you, which five algorithms are the most popular in machine learning?
- What are the different cases in which the algorithms of machine learning can be termed useful?
- How would you persuade someone to opt for machine learning when they have zero technical knowledge about the subject matter?
These are many more technical questions which can be asked of you. However, we have only mentioned these to give you an idea of what to expect during an interview. Always remember, when you are fully prepared for the interview, you can confidently answer all the questions being asked and in return ask the interviewer questions as well. Not only does it show your confidence, but also indicates that you possess detailed knowledge about the topic.
It is always better to remain updated about the latest certifications and what changes might be occurring in them. For more details, browse our information security course catalog to see the cyber security courses, classes, certification training and boot camps we have on offer. Not only will it help you in making an informed decision but also help you in identifying other certifications to upgrade your skill set.
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