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Introduction and Housekeeping

AWS ML Specialty Certification Exam Overview (Lesson 4)

Exam Purpose

  • Validates the ability to build, train, tune, and deploy ML models using AWS.
  • Translates business problems into ML solutions with justifications.
  • Identifies appropriate AWS services for implementing solutions.
  • Designs and implements scalable, cost-optimized, reliable, and secure ML solutions.

Candidate Profile

  • 1-2 years of AWS experience developing ML solutions.
  • Understanding of ML algorithms and hyperparameter optimization.
  • Hands-on experience with ML frameworks like scikit-learn and TensorFlow.
  • Knowledge of model training and deployment best practices.

Exam Guide Highlights

  • Exam Resources: AWS provides an exam guide and sample questions.
  • Question Format: Multiple choice and multiple response questions.
  • Scoring: Range between 100 to 1000 with a minimum passing score of 750.
  • Domains: Data Engineering, Exploratory Data Analysis, Modeling, Implementation and Operations.
  • Section Level Feedback: Given post-exam to indicate performance in each domain.

Domains and Weights

  • Data Engineering: Data repositories creation, data ingestion, and transformation.
  • Exploratory Data Analysis: Cleaning and preparing data for modeling.
  • Feature Engineering: Adding and creating relevant features.
  • Modeling: Framing business problems as ML problems, selecting algorithms, training, and evaluating models.
  • Implementation and Operations: Deploying solutions, ensuring availability, scaling, fault tolerance, security, and monitoring.

Preparation Tips

  • Real Complexity: Actual exam complexity may be underrepresented by listed resources.
  • AWS Knowledge: Approximately 15% of questions focus on general AWS knowledge.
  • Machine Learning Concepts: About 50-60% of questions test ML concepts that are not AWS-specific.
  • AWS ML Offerings: Around 25-35% of questions pertain to AWS-specific ML services and best practices.
  • Sample Questions: AWS provides a sample question PDF to identify strengths and improvement areas.

Exam Format

  • Duration: 170 minutes.
  • Number of Questions: Approximately 65.
  • Time Allocation: Roughly 2.5 minutes per question.

Conclusion

  • The exam is focused on developing professionals capable of solving business problems with ML on the AWS cloud.
  • It assesses not just AWS-specific knowledge but also a deeper understanding of machine learning concepts and their practical application.

References

AWS Machine Learning Specialty Exam Preparation (Lesson 6)

For AWS Beginners

  • Course Requirement: No prior AWS experience needed.
  • Follow Course: Complete all lectures and labs in sequence.

Starting Certification

  • Recommended First Step: AWS Cloud Practitioner certification for AWS basics.

Cost Benefits

  • Cost Savings: Cloud Practitioner exam can lead to discounts on the ML Specialty exam.

Machine Learning Knowledge

  • Framework Proficiency: Get familiar with scikit-learn.
  • Reference Book: "Introduction to Machine Learning with Python" by Andreas Müller.

AWS Resources

  • Free Training: Utilize AWS's "Machine Learning Basics" video and other free resources.

Practice Exams

  • Course Practice Exam: Take the full-length timed exam included in the course.
  • AWS Practice Exam: Available for purchase or free with a voucher.

Final Steps

  • Exam Registration: Use any vouchers for discounts on the ML Specialty exam.
  • Final Review: Address any gaps identified in practice exams.

AWS Account Setup, Free Tier Offers, Billing, Support (Lesson 7)

AWS Account Setup

  • Sign up at aws.amazon.com.
  • AWS provides hands-on experience with three types of free offers: always free, 12 months free, and trials.

Free Tier Offers

  • 12 Months Free: Access to certain AWS services like EC2 (T2/T3 micro), 5GB S3 storage, and 750 hours/month of RDS.
  • Free Trials: Short-term trials for services like Amazon SageMaker (2 months free).
  • Always Free: Services like DynamoDB offer a perpetual free tier up to a certain limit.

Post-Free Tier

  • Usage exceeding free tier limits or post-expiration incurs standard rates.

Root Account

  • The initial account created is the root account, with the highest privileges.

Billing and Charges

  • AWS automatically charges the payment method based on monthly usage.
  • Use the billing dashboard for a consolidated view of charges.
  • View detailed statements for an itemized list of charges.
  • Contact AWS support for billing inquiries or to dispute charges.

AWS Support

  • Billing Support: Available to all customers for billing-related queries.
  • Technical Support: Requires enrollment in a paid plan. Free support is available for account and billing support.

Service Quotas

  • AWS imposes service quotas (formerly service limits) to prevent unexpected charges.
  • Default quotas can be increased upon request if you hit a service limit error.

Billing Alerts, Delegate Access (Lesson 8)

Enabling Billing Dashboard Access

  • Billing dashboard is initially only accessible by the root account.
  • To delegate access, activate IAM user and role access to billing information in account settings.

Setting Up Billing Alerts

  • Navigate to Billing Preferences.
  • Enable alerts for approaching free tier limits and for billing alerts.

Creating a Billing Alarm with CloudWatch

  • Use CloudWatch in the North Virginia region to set up billing alarms.
  • Create an alarm for when estimated charges exceed a set threshold (e.g., $5).

Email Notifications

  • Set an action to email when the alarm triggers.
  • Create a new topic in Simple Notification Service (SNS) and add email addresses for alerts.

Using AWS Budgets for Tracking

  • AWS Budgets can track actual charges and forecast trends.
  • Set a monthly budget and receive alerts at specified thresholds (e.g., 50% of the budget).

Instructions - Configure IAM Users, Setup CLI (Lesson 9)

Step 1: IAM User Setup

  1. Root Login: Use root credentials to log in.
  2. IAM Service: Locate IAM Service in the AWS console.
  3. Account Alias:
    • Create an Account Alias for easier user sign-in.
    • Note down the IAM Users sign-in URL.
  4. Root Account MFA: Set up Multi-Factor Authentication for the root account.

Step 2: Create my_admin User

  1. User Creation:
    • Go to IAM Users.
    • Click Add Users.
    • User details:
      • Name: my_admin
      • Access type: Management Console
      • Password: Choose a custom password.
      • Uncheck "User must create a new password at next sign-in".
  2. Permissions:
    • Attach the AdministratorAccess policy directly.
  3. Finalize:
    • Create the user.
    • Securely save the sign-in credentials.

Step 3: Sign-out of Root Account

  • Log out from the root account.

Step 4: Sign-in as my_admin

  • Use the previously saved sign-in URL and credentials to log in as my_admin.

Step 5: Setup prediction_only User Permissions

  • Create Policy for SageMaker:
    • Navigate to IAM Policies.
    • Click Create policy.
    • Service: Choose SageMaker.
    • Permissions: Select "All read actions" under Read.
    • Resources: Select "All resources".
    • Name the policy SageMakerInvokeEndpoint.

Step 6: Create ml_user_predict

  1. User Creation:
    • In IAM, select Users then Add users.
    • User details:
      • Name: ml_user_predict.
  2. Attach Policies:
    • Attach SageMakerInvokeEndpoint.
    • Attach AmazonS3ReadOnlyAccess.

Step 7: Configure CLI for ml_user_predict

  1. Access Keys:
    • In the ml_user_predict user details, go to the Security Credentials tab.
    • Create an access key under the Access keys section.
  2. CLI Configuration:
    • Use the access key to configure the AWS CLI.
    • Follow video instructions [8:54 onwards] for CLI setup.
  3. Download Credentials:
    • Download the .csv file containing the access key for the ml_user_predict.

Benefits of Cloud Computing (Lesson 12)

  1. Cost Savings: Cloud offers a pay-as-you-go model, eliminating upfront capital investment.

  2. Visibility and Control: AWS provides tools like AWS Bills, Budgets, Cost Explorer, Cost and Usage Reports, and Cost Allocation Tags for monitoring and managing costs.

  3. Bulk Purchasing and Shared Infrastructure: Cloud providers negotiate better terms due to bulk purchases and shared customer infrastructure, reducing costs.

  4. Capacity Flexibility: The cloud allows for scaling resources based on actual demand, avoiding over or under capacity.

  5. Increased Speed and Agility: Resources can be spun up in minutes, fostering rapid experimentation and innovation at a lower cost.

  6. Eliminate Data Center Operations: Outsourcing infrastructure management to the cloud saves money and allows businesses to focus on differentiating activities.

  7. Global Reach: AWS's global data center network enables businesses to deploy applications close to customers worldwide, quickly and efficiently.

AWS Global Infrastructure Overview (Lesson 13)

AWS Cloud Types

  1. Public Cloud: Accessible at aws.amazon.com.
  2. US Gov Cloud: For US entities meeting specific security and compliance standards.
  3. China Cloud: Complies with China's legal and regulatory requirements.

AWS Global Presence

  • Regions: AWS has multiple isolated regions worldwide.
  • Benefits:
  • Proximity to customers for faster response times.
  • Compliance with data locality laws in different countries.

Data Storage and Transfer

  • Data stored in the selected AWS region.
  • Customer-initiated data replication across regions is possible.

Availability Zones (AZs)

  • Each region contains multiple AZs, each a collection of data centers.
  • AZs are physically separate but interconnected for redundancy.
  • Spreading applications across AZs enhances availability and protection.

Region and AZ Failures

  • AWS design ensures regional outages don't impact other regions.
  • Example strategies:
  • S3 copies data across AZs.
  • Elastic Load Balancer distributes traffic among healthy web servers in different AZs.
  • RDS uses primary and standby servers in different AZs for databases.

Multi-Region Deployment

  • Companies like Netflix deploy in multiple regions for higher availability.

Edge Locations

  • Over 200 Edge locations support CloudFront for low-latency content delivery.

AWS Outpost

  • Brings AWS services to on-premises data centers for low latency and critical use cases.

AWS Service Health Dashboard

  • Provides global and personalized health status of AWS services and resources.

Best Practice

  • Deploy applications across multiple AZs for enhanced reliability.