Learning Path

Aws Certification Path

AWS Data & ML Engineer focus on AWS Analytics and ML service offerings such as Amazon Kinesis, AWS Glue, Amazon Redshift, Amazon EMR, Amazon Athena, Amazon SageMaker, and more. AWS Data & ML Engineer design flexible and scalable solutions, and work on some of the most complex challenges in large-scale computing by utilizing skills in data structures, algorithms, and object-oriented programming.

2 Courses
32 Hours in Total
6 Case Studies
Lifetime access to course Content

Market Opportunity

Machine learning (ML) is one of the fastest-growing areas in technology and a highly sought after skillset in today’s job market. The World Economic Forum states the growth of artificial intelligence (AI) could create 58 million net new jobs in the next few years, yet it’s estimated that currently there are 300,000 AI engineers worldwide, but millions are needed.

Career Opportunity

The average salary of an AWS-certified professional is $129,868—ranking as one of the highest-paying certification categories in North America according to Global Knowledge IT Skills and Salary Report.

Rare skills

What You Will Learn

  • AWS Services and Algorithms
  • Amazon SageMaker, Amazon S3 Storage services, AWS Glue
  • AWS Kinesis Services (Kinesis firehose, Kinesis video streams, Kinesis data streams, Kinesis analytics)
  • Redshift, Redshift Spectrum, DynamoDB, Athena, Amazon Quicksight, Elastic Map Reduce (EMR)
  • Rekognition, Lex, Polly, Comprehend, Translate, transcribe, BlazingText Word2Vec, DeepAR, Factorization Machines, Gradient Boosted Trees (XGBoost)
  • Image Classification (ResNet), IP Insights, K-Means Clustering, K-Nearest Neighbor (k-NN)
  • Latent Dirichlet Allocation (LDA), Linear Learner (Classification), Linear Learner (Regression)
  • Neural Topic Modelling (NTM), Object2Vec, Object Detection, Principal Component Analysis (PCA), Random Cut Forest, Semantic Segmentation, and Seqence2Sequence
  • Train and deploy AI/ML models using AWS SageMaker
  • Develop and deploy a sentiment analysis model using SageMaker.

AWS Machine Learning Certification Exam | 2020 Complete Guide
1
17 hours
AWS SageMaker Practical for Beginners | Build 6 Projects
2
15 hours

Other Learning Paths

The new powerful tool that will guide you on your educational journey and empower your career with Data Science.

Machine Learning Skill Track

A machine learning (ML) engineer is an expert on using data to training models. The models are then used to automate processes like image classification, speech recognition, and market forecasting.

Learn More

Become a Deep Learning Engineer

A Deep Learning engineer builds models using deep learning neural networks to draw business insights, which can be used to make business decisions.

Learn More