| Question | Answer |
| Machine Learning Scientist – Quiz Module 1 | |
| Question 1: Supervised learning uses training data that includes the desired output. True False | True |
| Question 2: What is the Amazon Core Machine Learning team? Center of Excellence for applying machine learning approaches and technologies All answers Consults across different businesses to innovate on behalf of our customers a team that embraces ambitious opportunities | All answers |
| Question 3: Using the scenario below order each task as Step 1, Step 2, etc. to complete the scenario activity. Scenario: Using the Amazon ML console create a datasource, build a machine learning (ML) model, and use the model to generate predictions. Create an ML Model Prepare Your Data Create a Training Datasource Clean Up Review the ML Model’s Predictive Performance and Set a Score Threshold Use the ML Model to Generate Predictions | Step 3 → Step 1 → Step 2→Step 6 → Step 4 → Step 5 |
| Question 4: In Amazon Machine Learning, there are two ways to use a model to make predictions: batch predictions and online predictions. True False | True |
| Question 5: Amazon Machine Learning learns the non-linear type ML model. True False | True |
| Machine Learning Scientist – Quiz Module 2 | |
| Question 1: DeepLearning AMIs are part of the infrastructure/frameworks layer of the AI/ML Stack. True False | True |
| Question 2: Amazon Lex is part of the API-based application services in the Amazon AI/ML Stack. True False | True |
| Question 3: The Amazon AI/ML Stack is designed with which three levels: Application Services, Platform Services, Infrastructure/Framework Services Database Services, Application Services, Infrastructure/Framework Services Application Services, Database Services, Algorithm Services Compute Services, Application Services, Database Services | Application Services, Platform Services, Infrastructure/Framework Services |
| Question 4: The following services are part of the top layer/application services of the AI/ML Stack (select all that apply): Rekognition Lex Polly Translate Sagemaker | Rekognition Lex Polly Translate |
| Question 5: The following services are part of the platform services of the AI/ML Stack (select all that apply): Sagemaker DeepLens MachineLearning Tensorflow | Sagemaker DeepLens MachineLearning |
| Machine Learning Scientist – Quiz Module 2 (Second test) | |
| Question 1: API-based services in the Amazon AI/ML Stack are designed for application development. True False | True |
| Question 2: Amazon Machine Learning provides visualization tools and wizards that guide you through the process of creating machine learning (ML) models. True False | True |
| Question 3: AWS has created a suite of artificial intelligence and machine learning services that are referred to as the: AI/ML Stack AI Funnel AI/ML Tower AI/ML Stock | AI/ML Stack |
| Question 4: Which of the following operations make up the process of building ML models with Amazon Machine Learning? (select all that apply) data analysis model training evaluation reporting | data analysis model training evaluation |
| Question 5: The bottom layer of the AI/ML Stack include the following feature(s) (select all that apply): Ability to use any framework Create managed, auto-scaling clusters Run inference on trained models Conversational services | Ability to use any framework Create managed, auto-scaling clusters Run inference on trained models |
| Machine Learning Scientist – Final Assessment | |
| Question 1: Which of the following are examples of ways Amazon has been using machine learning? Supply chain, forecasting, and capacity planning Recommendations engine All answsers Paths that optimize robotic picking routes in fulfillment centers | All answsers |
| Question 2: Amazon Machine Learning learns the non-linear type ML model. True False | True |
| Question 3: What is the Amazon Core Machine Learning team? Consults across different businesses to innovate on behalf of our customers a team that embraces ambitious opportunities Center of Excellence for applying machine learning approaches and technologies All answers | All answers |
| Question 4: Put in order the general steps to build an ML Application: Frame the core ML problem(s) Feed the resulting features to the learning algorithm to build models and evaluate the quality of the models Construct more predictive input representations or features from the raw variables Use the model to generate predictions Collect, clean, and prepare data | 1. Frame the core ML problem(s) 2. Collect, clean, and prepare data 3. Construct more predictive input representations or features from the raw variable 4. Feed the resulting features to the learning algorithm to build models and evaluate the quality of the models 5. Use the model to generate predictions |
| Question 5: API-based services in the Amazon AI/ML Stack are designed for application development. True False | True |
| Question 6 The top layer of the AI/ML Stack include: All answers Language services Vision services Conversational services | All answers |
| Question 7: The following services are part of the top layer/application services of the AI/ML Stack (select all that apply): Sagemaker Rekognition Lex Polly Translate | Rekognition Lex Polly Translate |
| Question 8: Amazon Machine Learning provides visualization tools and wizards that guide you through the process of creating machine learning (ML) models. True False | True |
| Question 9: The key distinction between a Data Analyst and a Machine Learning Engineer has to do with: running algorithms active stock price the end goal producing visualizations | the end goal |
| Question 10: A formal characterization of probability (conditional probability, Bayes rule, likelihood, independence, etc.) and techniques derived from it (Bayes Nets, Markov Decision Processes, Hidden Markov Models, etc.) are at the heart of many Machine Learning algorithms; these are a means to deal with uncertainty in the real world. True False | True |
| Question 11: Select three (3) skills listed below that are necessary for a successful machine learning engineer: data modeling and evaluation infrastructure management probability and statistics software engineering and system design | data modeling and evaluation probability and statistics software engineering and system design |
| Question 12: Data modeling is the process of estimating the underlying structure of a given dataset, with the goal of finding useful patterns (correlations, clusters, etc.) and/or predicting properties of previously unseen instances (classification, regression, anomaly detection, etc.) True False | True |
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