Artificial Intelligence (AI) is transforming industries, and machine learning sits at its core. As organisations increasingly adopt AI, skilled professionals who can build and deploy ML solutions on the cloud are in high demand. An AWS Machine Learning Certification validates your expertise in this field and elevates your career opportunities.
This article covers obtaining this credential and succeeding in the thriving AI sector.
AWS Machine Learning Certification: The Gateway to a Rewarding Career in AI
The rapid advancement of artificial intelligence (AI) and machine learning has created many new job opportunities. However, more people need the right skills to fill these jobs.
Getting certified in AWS Machine Learning sets you apart as someone who can create, teach, and use machine learning systems on the AWS cloud. This certification makes you very valuable to employers who need skilled machine-learning experts to make their AI dreams a reality.
Why is AWS Machine Learning Certification Worth it?
The demand for machine learning professionals has surged, leading to a 344% increase in job postings over the past 5 years. Obtaining certification equips individuals with essential skills, significantly enhancing their resumes.
AWS Certified Machine Learning Specialists have reported a 27% increase in their average salary, with major industry players like Netflix, Airbnb, and NASA relying on AWS for machine learning.
This certification opens doors to diverse career opportunities, as employers recognise it as a mark of proficiency in ML algorithms, frameworks, and best practices. Therefore, AWS certification represents a strategic investment for a successful career in machine learning.
AWS Certified Machine Learning Specialty Certification Overview
The AWS Certified Machine Learning: Specialty certification proves your expertise in using machine learning on AWS. It shows you can create, train, optimise, and deploy ML models using Amazon SageMaker, AWS Lambda, Amazon S3, and other services.
It demonstrates your ability to build scalable, reliable, and cost-effective AWS ML solutions, making you valuable to organisations using machine learning on AWS.
AWS Machine Learning Specialty Certification Exam Syllabus
The exam focuses on four key domains:
- Data Engineering (20% weightage): Assessing skills in creating data stores, identifying sources, and ingestion solutions for machine learning using services like Amazon Kinesis and AWS Glue.
- Exploratory Data Analysis (24%): Evaluates data preparation capabilities, including dealing with missing/corrupt data, feature engineering, analysis, and visualisation.
- Modelling (36%): Tests framing business problems as ML challenges, differentiating between ML model types, optimisation techniques, and computing resource selection.
- Implementation & Operations (20%): Following best practices, the focus is building performant, scalable, and reliable ML solutions on AWS. It also assesses monitoring, troubleshooting, and cost optimisation.
AWS Machine Learning Certification Salary
Individuals with AWS credentials earn between ₹91,20,000 and ₹1,06,40,000 annually. However, AWS Certified Machine Learning Specialists, in particular, take home an average salary of ₹96,53,312 per year, demonstrating the financial upside of skilling up in this domain.
AWS Machine Learning Certification: Prerequisites and Exam Details
Prerequisites:
- 2 years of hands-on experience with ML workloads on AWS
- Understanding of core machine learning algorithms
- Hyperparameter optimisation skills
- Proficiency in ML frameworks like TensorFlow, PyTorch
- Expertise in model training, deployment, ops best practices
Exam Details:
- Level: Specialty
- Duration: 3 hours
- Cost: ₹22,500
- Total Questions: 65 (50 scored + 15 unscored)
- Passing Score: 750 out of 1,000
How to Prepare for the AWS Machine Learning Certification Exam?
Follow this 5-step guide:
- Learn meaningful machine learning and Amazon Web Services (AWS) skills by taking courses and doing practical projects.
- Get instructor guidance while learning about AWS tools for Deep Learning and building Machine Learning solutions.
- Gain hands-on experience by working on real-world machine learning projects using AWS.
- Practice for the exam to make sure you’re ready.
- Schedule and pass the exam to show your machine learning and AWS skills.
Augment the above with:
- Increased hands-on exposure
- Working with actual data
- Learning open-source ML libraries
- Active community participation
- Tracking AWS advancements
- Simulate exam conditions beforehand
- Effective time management during exam
Conclusion
The AWS Certified Machine Learning credential shows you’re good at creating and using AI programs on the AWS Cloud. Because there’s a significant need for people who know about AI, having this certification can help you get a good job in this exciting field. With a good plan, some help, and hard work, you can get this certification and open up new opportunities for your career.
