Exam Readiness: AWS Certified Machine Learning - Specialty

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Exam Readiness- AWS Certified Machine Learning - Specialty Course Overview

Enroll for the 1-day Exam Readiness: AWS Certified Machine Learning - Specialty certification training course from Koenig Solutions accredited by AWS. The AWS Certified Machine Learning – Specialty exam validates your ability to design, implement, deploy, and maintain Machine Learning (ML) solutions for given business problems. In this course you will learn how to prepare for the exam by exploring the exam’s topic areas including data engineering, exploratory data analysis, modeling, and machine learning implementation and operations.

Target Audience:

This course is intended for Machine learning practitioners who are preparing to take the AWS Certified Machine Learning - Specialty exam

Learning Objectives:

After completing this course, you will be able to:

  • Identify your strengths and weaknesses in each of the exam domains.
  • Create a subsequent study plan to prepare for the exam.
  • Describe the technical topics and concepts making up each of the exam domains.
  • Summarize the logistics and mechanics of the certification exam and its questions.
  • Identify effective test taking strategies that can be used to answer exam questions

 

The 1-on-1 Advantage

Methodology

Flexible Dates

  • • Choose Start Date
  • • Reschedule After Booking
  • • Weekend / Evening Option

4-Hour Sessions

You will learn:

Module 1: Exam Overview and Test-taking Strategies
  • Testing center information and expectations
  • Exam overview and structure
  • Content domains and question breakdown
  • Topics and concepts within content domains
  • Question structure and interpretation techniques
  • Practice exam questions
  • Domain 1.1: Data Repositories for machine learning
  • Domain 1.2: Identify and implement a data-ingestion solution
  • Domain 1.3: Identify and implement a data-transformation solution
  • Walkthrough of study questions
  • Domain 1 quiz
  • Domain 2.1: Sanitize and prepare data for modeling
  • Domain 2.2: Perform featuring engineering
  • Domain 2.3: Analyze and visualize data for ML
  • Walkthrough of study questions
  • Domain 2 quiz
  • Domain 3.1: Frame business problems as machine learning (ML) problems
  • Domain 3.2: Select the appropriate model(s) for a given ML problem
  • Domain 3.3: Train ML models
  • Domain 3.4 Perform hyperparameter optimization
  • Domain 3.5 Evaluate ML models
  • Walkthrough of study questions
  • Domain 3 quiz
  • Domain 4.1: Build ML solutions for performance, availability, scalability, resiliency, and fault tolerance
  • Domain 4.2: Recommend and implement the appropriate ML services and features for a given problem
  • Domain 4.3: Apply basic AWS security practices to ML solutions
  • Domain 4.4: Deploy and operationalize ML solutions Walkthrough of study questions Domain 4 quiz
Live Online Training (Duration : 8 Hours)
We Offer :
  • 1-on-1 Public - Select your own start date. Other students can be merged.
  • 1-on-1 Private - Select your own start date. You will be the only student in the class.

700 + If you accept merging of other students. Incl. Official Courseware
4 Hours
8 Hours
Comfort Track
Week Days
Weekend

Start Time : At any time

12 AM
12 PM

1-On-1 Training is Guaranteed to Run (GTR)
Group Training
650 Per Participant Incl. Official Courseware
Online
12 Dec
09:00 AM - 05:00 PM CST
(8 Hours/Day)
Online
16 Jan
09:00 AM - 05:00 PM CST
(8 Hours/Day)
Course Prerequisites
  • 1-2 years of hands-on experience developing, architecting, or running ML/deep learning workloads on the AWS cloud
  • Proficiency expressing the intuition behind basic machine learning algorithms and performing basic hyperparameter optimization
  • Understanding of the machine learning pipeline and its components
  • Experience with machine learning and deep learning frameworks
  • Understanding of and experience in model training, deployment and operational best practices

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FAQ's


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