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Test Number : MLS-C01
Test Name : AWS Certified Machine Learning Specialty (MLS-C01)
Vendor Name : Amazon
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MLS-C01 test Format | MLS-C01 Course Contents | MLS-C01 Course Outline | MLS-C01 test Syllabus | MLS-C01 test Objectives


Format : Multiple choice, multiple answer
Type : Specialty
Delivery Method : Testing center or online proctored exam
Time : 170 minutes to complete the exam

Introduction
The AWS Certified Machine Learning - Specialty (MLS-C01) examination is intended for individuals who perform a development or data science role. This test validates an examinees ability to build, train, tune, and deploy machine learning (ML) models using the AWS Cloud.
It validates an examinees ability to design, implement, deploy, and maintain ML solutions for given business problems. It will validate the candidates ability to:
=> Select and justify the appropriate ML approach for a given business problem.
=> Identify appropriate AWS services to implement ML solutions.
=> Design and implement scalable, cost-optimized, reliable, and secure ML solutions

Expectations;
- 1-2 years of experience developing, architecting, or running ML/deep learning workloads on 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

Exam Content
There are two types of questions on the examination:
=> Multiple choice: Has one correct response and three incorrect responses (distractors).
=> Multiple response: Has two or more correct responses out of five or more options.
Select one or more responses that best complete the statement or answer the question. Distractors, or incorrect answers, are response options that an examinee with incomplete knowledge or skill would likely choose. However, they are generally plausible responses that fit in the content area defined by the test objective.
Unanswered questions are scored as incorrect; there is no penalty for guessing.

Unscored Content
Your examination may include unscored items that are placed on the test to gather statistical information. These items are not identified on the form and do not affect your score.

Exam Results
The AWS Certified Machine Learning - Specialty (MLS-C01) examination is a pass or fail exam. The examination is scored against a minimum standard established by AWS professionals who are guided by certification industry best practices and guidelines.
Your results for the examination are reported as a score from 100–1,000, with a minimum passing score of 750. Your score shows how you performed on the examination as a whole and whether or not you passed. Scaled scoring models are used to equate scores across multiple test forms that may have slightly different difficulty levels.

Domain 1: Data Engineering 20%
Domain 2: Exploratory Data Analysis 24%
Domain 3: Modeling 36%
Domain 4: Machine Learning Implementation and Operations 20%
TOTAL 100%

Domain 1: Data Engineering
1.1 Create data repositories for machine learning.
1.2 Identify and implement a data-ingestion solution.
1.3 Identify and implement a data-transformation solution.

Domain 2: Exploratory Data Analysis
2.1 Sanitize and prepare data for modeling.
2.2 Perform feature engineering.
2.3 Analyze and visualize data for machine learning.

Domain 3: Modeling
3.1 Frame business problems as machine learning problems.
3.2 Select the appropriate model(s) for a given machine learning problem.
3.3 Train machine learning models.
3.4 Perform hyperparameter optimization.
3.5 Evaluate machine learning models.

Domain 4: Machine Learning Implementation and Operations
4.1 Build machine learning solutions for performance, availability, scalability, resiliency, and fault tolerance.
4.2 Recommend and implement the appropriate machine learning services and features for a given problem.
4.3 Apply basic AWS security practices to machine learning solutions.
4.4 Deploy and operationalize machine learning solutions.



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Amazon proclaims global enlargement of its Contact core Intelligence tools | MLS-C01 test questions and PDF Download

Amazon internet capabilities Inc. is increasing the focal point of its Contact middle Intelligence features that valued clientele can use to add synthetic intelligence capabilities to their contact center operations.

AWS CCI can now be used with client’s existing contact core providers to carry new efficiencies, create more personalized consumer journey and get deeper insights from facts, AWS spoke of.

Launched last summer time, AWS CCI is a combination of functions that permits businesses to deliver machine discovering capabilities together with text-to-speech, language comprehension, translation, business search, company intelligence and chatbots to their contact centers. These capabilities may also be used to assist with initiatives corresponding to self-carrier, live-call analytics and agent aid, and post-name analytics as an example.

AWS is also expanding its world support for CCI and making it accessible to be used in pre-configured options attainable from participating Amazon accomplice network companions that offer contact core workflow tools.

The AWS CCI Self-service solution is now purchasable in dissimilar languages, together with French, German, Italian and Spanish, the company observed. It makes use of computing device discovering-based mostly chatbots and interactive voice response to tackle and deflect standard queries and tasks, in order that human operators can focus on more stressful interactions that robots can’t address.

The provider relies on the conversational interface of Amazon Lex and Amazon Polly’s text-to-speech voices to create a dynamic virtual agent that can talk distinctive languages. Amazon Kendra helps make these brokers smarter with the aid of discovering answers to caller’s questions from internal advantage bases.

The live name Analytics & Agent assist and submit-call Analytics capabilities at the moment are supported all through Europe. They use Amazon Transcribe to transcribe calls in actual-time or put up-name.

Amazon comprehend then analyzes these interactions, detects name sentiment and identifies keywords and phrases in the dialog the use of herbal language processing. Amazon Kendra can take these key words and intelligently seek well timed tips agents can use to get to the bottom of are living call issues, AWS stated.

AWS CCI has additionally delivered new language expansions for Amazon Lex, Amazon Transcribe and Amazon Translate. in addition, transcription of are living calls is now purchasable in German, Italian, jap, Korean and Portuguese, AWS said. Amazon Translate has been extended too and can now translate calls into an agent’s favored language, with support for 16 new languages bringing the overall up to 71.

“With AWS CCI, they wanted to make it handy for purchasers who use distinct contact facilities suppliers so as to add AI and obtain new tiers of operational effectivity,” defined Vasi Philomin, time-honored supervisor of AWS Language services. “Having a worldwide associate network is critical to enabling their customers to recognise the advantages of cloud-primarily based computing device discovering functions and putting off the deserve to employ really expert developers to construct and maintain these systems.”

AWS pointed out its technology partners at launch include Salesforce.com Inc., Avaya Inc., Talkdesk Inc., eightĂ—eight Inc., Clarabridge Inc., Clevy SAS, XappMedia, Inc. and Voiceworx Inc.

some of these partners had been wanting to talk. Talkdesk talked about it’s the usage of AWS CCI to add new capabilities its computing device gaining knowledge of-based mostly contact middle equipment. It noted its consumers can use the AWS CCI functions together with Talkdesk iQ’s native AI components. furthermore, it spoke of, the Talkdesk Agent support and Talkdesk Speech Analytics functions now each leverage Amazon Transcribe to prolong the number of languages and accents they can aid.

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