Welcome to the Nanodegree program

Introduction to Software Engineering

In this lesson, you’ll write production-level code and practice object-oriented programming, which you can integrate into machine learning projects.

Software Engineering Practices Pt I

Software Engineering Practices Pt II


Portfolio Exercise: Upload a Package to PyPi

Cloud Computing

Introduction to Deployment

Learn how to deploy machine learning models to a production environment using Amazon SageMaker.

Building a Model using SageMaker

Implement and use a mode

04. Hyperparameter Tuning

Updating a Model

Project: Deploying a Sentiment Analysis Model

Population Segmentation

Apply machine learning techniques to solve real-world tasks; explore data and deploy both built-in and custom-made Amazon SageMaker models.

Payment Fraud Detection

Interview Segment: SageMaker

Deploying Custom Models

Time-Series Forecasting


Introduction to NLP

Learn Natural Language Processing one of the fields with the most real applications of Deep Learning

Implementation of RNN _ LSTM

Sentiment Prediction RNN

Convolutional Neural Networks

Transfer Learning

Weight Initialization


Job Search

Find your dream job with continuous learning and constant effort

Refine Your Entry-Level Resume

Craft Your Cover Letter

Optimize Your GitHub Profile

Develop Your Personal Brand

10. Cleaning Up Your AWS Account

Once you have finished making use of Amazon’s services you should make sure to clean up your account. One of the main reasons for this is so that you don’t get an unexpected bill!

Have you cleaned up?

Task List:

Shut down any notebook instances that are running.

Shut down any endpoints that are running.

Clean up your S3 buckets, provided you are finished with them. Note: Deleting an S3 bucket can not be undone so only do this if you are completely finished.

Delete any unused Lambda functions.

Remove any unused APIs created using API Gateway


Task Feedback:

It is generally a good idea to double check your AWS account from time to time as you are working with various services. Keep your AWS account tidy!