Udacity AWS Machine Learning Engineer Nanodegree - Full Review
The Fall of the finest self-learning educational institution on the planet
The Syllabus:
Course 1: Introduction to Machine Learning
Course 2: Developing Your First ML Workflow
Course 3: Deep Learning Topics within Computer Vision and NLP
Course 4: Operationalizing Machine Learning Projects on SageMaker
CAPSTONE PROJECT
Introduction:
In this nanodegree, Udacity tries to provide a nanodegree for machine learning and an AWS Cloud ecosystem for machine learning and data science. This nanodegree no. 5 for me on Udacity and the review came out of the need that someone should talk as Udacity will try to silence the counter voices and will not show their reviews on its website.
Instructors:
Matt Maybeno
Joseph Nicolls
Charles Landau
Soham Chatterjee
Bradford Tuckfield
The instructors use AWS and machine learning but are not cloud experts specialized in ML cloud solutions. They just use it in their work and research.
Projects:
Project 1: Predict Bike Sharing Demand With AutoGluon:
The project aims to familiarize the students with the open-source Auto ML library.
(Good project for learning AutoGluon)
Project 2: Build an ML Workflow For Scones Unlimited on Amazon
The project aims to build and ship an image classification model on AWS SageMaker
(Good Project for starting using SageMaker)
Project 3: Image Classification using AWS SageMaker
The project aims to use Sagemaker with deep-learning models
(One of the worst projects on Udacity you will discover that the project will not be complete without the inference script). Did they mention it in the course? No. Did they put it as a part of the starter scripts of the project? No. They will surprise you that you need it later and without it, the endpoint will not be able to handle the images for inference.
Project 4: Operationalizing an AWS ML Project
(Similar to the previous project but with more details, and more screenshots because they will not believe you.)
Capstone Project: You can select to carry out a premade project or a custom project of your choice. The project consists of two parts (First Part: proposal - Second Part: Implementation)
Pros & Cons:
Pros:
- Cannot find any pros.
Cons:
- The nanodegree tries to explain machine learning and the AWS ecosystem for machine learning and they failed at both. They barely touched the surface. The nanodegree did not of into depth in any part. You can say this nanodegree is just a revision of some information that you know about AWS. I found that AWS documentation, tutorials, SkillBuilder platform, and AWS classroom paid lessons are far more valuable and better than this nanodegree.
- The last 3 projects are just repeated projects, the only difference is just some additional requirements.
- The given AWS accounts to use Sagemaker have $25 limits. Once you hit the limit you will not be able to use it anymore. The cloud gateway will keep loading forever. If you ran out of accounts and credits, you will be obligated to continue on a personal account from your side.
- In each course, you will be given a brand new AWS account. Make sure you keep local backups in case your cloud gateway kept loading forever.
- There are no career services if you are a part of enterprise grants.
- The students' forums have no mentors to answer your questions. I personally posted a problem, but they never answered. Also, you can read other posts and you will find rare posts with mentor answers or none.
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