Kirill Eremenko and Hadelin de Ponteves discuss the importance of learning cloud computing for data scientists, essential AWS services, database options, running analytics, and the benefits of AWS certification on the podcast.
Acquiring AWS certification enhances data scientists' credibility and opens up career opportunities.
Employers seek AWS certified professionals for cloud-related roles, showcasing proficiency in AWS technologies.
Utilizing AWS services like SageMaker for machine learning simplifies model development and deployment for data scientists.
Deep dives
The Importance of Cloud Computing for Data Scientists
Working with cloud computing platforms like AWS, Azure, and Google Cloud is essential for data scientists, allowing them to scale up infrastructure efficiently. AWS offers services like EC2 for compute, S3 for storage, Redshift for databases, and SageMaker for machine learning.
AWS Certification and Career Advancement
Acquiring AWS certification adds credibility to a data scientist's skills, showcasing expertise in cloud services. Employers look for certified professionals for cloud-related positions, enhancing career opportunities and demonstrating proficiency in AWS technologies.
Diversified Machine Learning Tools in AWS
Besides SageMaker, AWS offers various machine learning tools like DeepRacer for reinforcement learning, Augmented AI for human review, Forecast for time series predictions, Translate for machine translation, Comprehend for NLP, and Recognition for object detection.
Benefits of Using AWS Services
Utilizing AWS services like SageMaker's SDK and AutoML streamlines machine learning model development, providing options for easy code-free model building, ensembling, hyperparameter tuning, training, and deployment, with endpoints for prediction deployment.
Data Science Community on CloudWolf
Kirill and Adlenn are launching CloudWolf, a platform for cloud education and a community hub. They offer courses on AWS certification, data science in the cloud with hands-on exercises, study materials, and practice exams, fostering interactive learning.
Get to grips with AWS, Azure, Google Cloud Platform on this week’s episode. Host Jon Krohn speaks with Kirill Eremenko and Hadelin de Ponteves about CloudWolf, a cloud computing educational platform that prepares students for certification in AWS (Amazon Web Services). Find out why an accreditation in cloud computing could be the safest investment for your data science career.
This episode is brought to you by Posit, the open-source data science company, and by AWS Inferentia. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.
In this episode you will learn: • About CloudWolf [07:04] • Why learning the cloud is important for data scientists [09:12] • Is learning cloud computing complex? [22:30] • Essential AWS services [28:31] • Database options on AWS [33:47] • How to run analytics on AWS [40:58] • Why an AWS certification is so helpful [56:35]