AWS Certified Machine Learning Speciality Exam Prep

The AWS Certified Machine Learning - Specialty Exam Prep Course is a comprehensive training program designed to prepare participants for the AWS Certified Machine Learning - Specialty (MLS-C01) certification exam.

This course focuses on developing the skills and knowledge necessary to understand machine learning, including the concepts of data engineering, exploratory data analysis, modeling, and machine learning implementation and operations.

Throughout the course, participants will delve into the core principles of machine learning on the Amazon Web Services (AWS) platform. They will gain in-depth knowledge of AWS machine learning services, including understanding and differentiating the key features of AWS machine learning services, and analyzing needs and requirements to design and recommend appropriate machine learning solutions using AWS services.

Each module of the course covers the exam domains and objectives, providing detailed explanations, real-world examples, and hands-on exercises. Participants will have the opportunity to work with AWS services, select appropriate machine learning approaches for specific business problems, design, build, deploy, optimize, train, tune, and maintain machine learning solutions for given business problems in a live AWS environment.

The course includes interactive discussions, practical demonstrations, and opportunities for participants to ask questions and clarify their understanding. Sample exam questions and practice exercises are incorporated to reinforce learning and help participants become familiar with the exam format.

By the end of this course, participants will be well-prepared to tackle the AWS Certified Machine Learning - Specialty exam with confidence.

• Data Scientists
• Machine Learning Engineers
• AI Engineers
• Professionals who work with machine learning in a cloud environment
• Individuals in an artificial intelligence/machine learning (AI/ML) role with at least one to two years of hands-on experience
• Professionals who are proficient in designing and implementing ML solutions to solve practical business problems

• A minimum of 2 or more years of hands-on experience developing, architecting, and running ML or deep learning workloads in the AWS Cloud
• The ability to express the intuition behind basic ML algorithms
• Experience performing basic hyperparameter optimization
• Experience with ML and deep learning frameworks
• The ability to follow model-training best practices
• The ability to follow deployment and operational best practices

• Comprehensive Course Material: Detailed course content covering all four domains of the MLS-C01 exam: Data Engineering, Exploratory Data Analysis, Modeling, and Machine Learning Implementation and Operations
• Hands-On Exercises: Practical exercises and labs that provide real-world experience with AWS machine learning services and concepts, such as creating data repositories, implementing data ingestion and transformation solutions, sanitizing and preparing data for modeling, performing feature engineering, and analyzing and visualizing data for machine learning
• Interactive Discussions: Opportunities for students to engage in discussions, ask questions, and clarify doubts about AWS services and machine learning practices
• Real-World Examples: Case studies and examples that illustrate how the concepts learned are applied in real-world scenarios, such as framing business problems as machine learning problems, selecting appropriate models for given machine learning problems, training machine learning models, performing hyperparameter optimization, and evaluating machine learning models
• Practice Questions: A set of practice questions or mock exams to help students gauge their understanding of the material and their readiness for the actual exam
• Exam Preparation Guidance: Tips and strategies for preparing for and taking the MLS-C01 exam, including understanding the exam format and how to manage time during the exam
• Access to Course Instructor or Support: Depending on the course provider, students may have access to the course instructor or a support team to help with any questions or issues that arise during the course
• Certificate of Completion: Upon successful completion of the course, students typically receive a certificate of completion.