Become an AWS SageMaker Machine Learning Engineer in 30 Days — 93% Off Coupon

Build 30+ ML Projects in 30 Days in AWS, Master SageMaker JumpStart, Canvas, AutoPilot, DataWrangler, Lambda & S3

⭐ 4.6 out of 5(12,000 students enrolled)Created by Prof. Ryan AhmedLast updated: 🌐 English

Course Overview - Key Takeaways

The following summarizes all verified data points for this course, including pricing, duration, instructor, and coupon validity. All data is sourced directly from Udemy and verified by CourseSpeak on .

•Course Title: Become an AWS SageMaker Machine Learning Engineer in 30 Days
•Provider: Udemy (listed via CourseSpeak)
•Instructor: Prof. Ryan Ahmed
•Coupon Verified On: August 17, 2026
•Difficulty Level: Advanced
•Category: Development
•Subcategory: Amazon Sagemaker
•Duration: 43h of on-demand video
•Language: English
•Access: Lifetime access to all course lectures and updates
•Certificate: Official certificate of completion issued by Udemy upon finishing all course requirements
•Top Learning Outcomes: Build, Train, Test and Deploy Machine Learning Models in AWS · Leverage ChatGPT and GPT-4 to Automate Coding Tasks, Perform Code Debugging, Write Documentation and Add New Features to your Code · Define and Perform Image and Text Labeling Jobs Using AWS SageMaker GroundTruth
•Prerequisites: Basic Python Programming Knowledge · Basic knowledge in AWS
•Price: $9.99 with coupon / Regular Udemy price: $149.99. Applying this coupon saves you $140.00 (93% OFF).
•Coupon: Click REDEEM COUPON below to apply discount
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What You'll Learn

This course gives you the following verified skills and competencies in Development:

✓Build, Train, Test and Deploy Machine Learning Models in AWS .
✓Leverage ChatGPT and GPT-4 to Automate Coding Tasks, Perform Code Debugging, Write Documentation and Add New Features to your Code .
✓Define and Perform Image and Text Labeling Jobs Using AWS SageMaker GroundTruth .
✓Prepare, Clean and Visualize data Using AWS SageMaker Data Wrangler without Writing any Code .
✓Optimize ML model hyperparameters using GridSearch, Bayesian & Random Search Optimization Techniques .
✓Master Key AWS services such as Simple Storage Service (S3), Elastic Compute Cloud (EC2), Identity and Access Management (IAM) and CloudWatch .
✓Understand Machine Learning workflow automation using AWS Lambda, Step functions and SageMaker Pipelines. .
✓Learn how to define a lambda function in AWS management console, understand the anatomy of Lambda functions, and how to configure a test event in Lambda .
✓Train a Machine Learning Regression and Classifier Models Using No-code AWS Canvas .
✓Learn how to leverage Amazon SageMaker Autopilot and SageMaker Canvas to train multiple models without writing any code. .
✓Perform Exploratory Data Analysis and Visualization Using Pandas, Searborn and Matplotlib Libraries .
✓Understand Regression Models KPIs Such as RMSE, MSE, MAE, R2 and Adjusted R2 .
✓Understand Classification Models KPIs such as Accuracy, Precision, Recall, F1-Score, ROC, and AUC .
✓Define a Machine Learning Training Job Using AWS SageMaker JumpStart .
✓Deploy an Endpoint Using Amazon SageMaker, Perform Inference and Generate Predictions .
✓Define a Lambda function using Boto3 SDK and Test the lambda function using Eventbridge (cloudwatch events) .
✓Understand the difference between synchronous and asynchronous Lambda Functions invocations .
✓Perform AI/ML Models Prototyping Using AutoGluon Library .
✓How to monitor billing dashboard, set alarms, S3/EC2 instances pricing and request service limits increase .
✓Understand the difference between Artificial Intelligence (AI), Machine Learning (ML), Data Science (DS) and Deep Learning (DL) .
✓Learn the fundamentals of Amazon SageMaker, SageMaker Components, training options including built-in algorithms, AWS Marketplace, & customized ML Algorithms .
✓Leverage a Yolo V3 Object Detection Algorithm available on the AWS Marketplace .
✓Understand the format and Use Case of Json Lines and Manifest Files .
✓Learn auto-labeling workflow and understand the difference between SageMaker GroundTruth and GroundTruth Plus .
✓Learn how to define a labeling job with bounding boxes (object detection), pixel-level Semantic Segmentation, and text data .
✓Understand the difference between data labeling workforces in AWS such as public mechanical Turks, private labelers and AWS curated third-party vendors .
✓Learn the difference between Supervised, Unsupervised and Reinforcement Machine Learning Strategies .
✓Perform data visualization using Seaborn & Matplotlib libraries, plots include line plot, pie charts, subplots, pairplots, countplots, and correlations heatmaps .
✓Export a data wrangler workflow into Python script, create a custom formula and apply it to a given column in the data, and generate summary tables/bias report .
✓Learn how to train an XG-boost algorithm in SageMaker using AWS JumpStart, assess trained model performance, plot residuals, & deploy an endpoint .
✓Understand Bias-Variance Trade-off, L1 and L2 Regularization Techniques .
✓Train/Test several ML Classifiers such as Logistic Regression, Support Vector Machine, K-Nearest Neighbors, Decision Trees, and Random Forest Classifiers .
✓Learn SageMaker Built-in Algorithms such as Linear Learner, XG-Boost, Principal Component Analysis (PCA), and K-Nearest Neighbors.

Course Requirements & Prerequisites

The following background knowledge and tools are recommended before starting this course. Students without these prerequisites may still enroll but should expect a steeper learning curve:

•Basic Python Programming Knowledge
•Basic knowledge in AWS
•Basic knowledge in machine learning

About This Udemy Course

The following is the full official course description as published on Udemy by instructor Prof. Ryan Ahmed. It covers the curriculum structure, teaching methodology, and topic scope for this Development course:

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Is the Become an AWS SageMaker Machine Learning Engineer in 30 Days Coupon Worth It?

Expert review by Josh Smith, Lead Course Reviewer at CourseSpeakUpdated Aug 17, 2026

The short answer is yes — provided the Development skills this course teaches actually line up with what you want to build. The regular price for Become an AWS SageMaker Machine Learning Engineer in 30 Days on Udemy is $149.99. The coupon code listed on this page drops that to $9.99 — a saving of $140.00, or 93% off the standard rate. Spread across 43h of on-demand video, that works out to roughly $0.23 per hour of content — less than the cost of a single chapter of most printed development textbooks.

A discount is only worth something if the material delivers, and the curriculum here is built around practical outcomes. Prof. Ryan Ahmed walks you through build, Train, Test and Deploy Machine Learning Models in AWS, leverage ChatGPT and GPT-4 to Automate Coding Tasks, Perform Code Debugging, Write Documentation and Add New Features to your Code, and define and Perform Image and Text Labeling Jobs Using AWS SageMaker GroundTruth — concrete skills you can apply, not abstract theory. It has already been taken by 12,000 students and holds a 4.6-star average from verified reviews, which is a reasonable sign the content holds up in practice.

The bar to entry is low: Basic Python Programming Knowledge; Basic knowledge in AWS. That makes it a realistic choice even if Development is unfamiliar territory. In practical terms, expect around 43h of on-demand video to work through at your own pace. The material is presented in English.

Pros

  • ✓Verified 93% price reduction.
  • ✓High learner satisfaction (4.6/5).
  • ✓Trusted by 12,000 students.
  • ✓Certificate + lifetime access.

Cons

  • !The coupon is time-limited — once it expires, the price tends to revert toward the standard $149.99.
  • !Lifetime access is tied to Udemy staying online; the platform can change its policies.
  • !Budget for the exercises and quizzes too — they add real time on top of the 43h of video.
JS
Josh Smith
Lead Course Reviewer
Credentials →

"At roughly $0.23 an hour of video, Become an AWS SageMaker Machine Learning Engineer in 30 Days is priced sensibly for what it actually covers — build, Train, Test and Deploy Machine Learning Models in AWS and beyond. If Development is on your roadmap and you value the 4.6-star track record, this coupon is worth using while it's still valid."

✓
Final Verdict: Worth It
Saves you $140.00 against the standard Udemy price
New to redeeming coupons? Visit our step-by-step guide for detailed instructions on how to apply coupon codes.Coupon last verified August 17, 2026.At $9.99 you save $140.00 compared to the standard $149.99 price, and Udemy coupons are time-limited — redeem as soon as possible.

Course Rating Summary

This course holds an aggregate rating of 4.6 out of 5 based on 12,000 student reviews on Udemy. The distribution below shows the approximate percentage of students who gave each star rating.

4.6
12,000 Verified Ratings
5 stars
75%
4 stars
15%
3 stars
6%
2 stars
2%
1 star
2%

* Rating distribution is approximated from the aggregate score. Sourced from Udemy. Last verified: August 17, 2026.

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Instructor Profile

Background information on Prof. Ryan Ahmed, the instructor responsible for this course on Udemy.

PR
Prof. Ryan Ahmed
Udemy Instructor
Full Profile ↗
Subject Area
Development
Total Students
12,000+ enrolled
Rating
4.6 / 5.0
Course Duration
43h
Teaching Approach
Practical, project-based instruction built around real-world application of Development skills, with hands-on exercises and quizzes to reinforce each section.

Frequently Asked Questions

The following questions and answers cover the most common queries about this course, its coupon code, pricing, and enrollment process. All answers are based on verified data from Udemy as of August 17, 2026.

About the Author

Josh Smith
Josh Smith
Udemy Coupon Specialist

8+ years finding and verifying the best Udemy deals. Helped thousands of students save on premium courses through curated coupon codes and exclusive discounts.