Practical Data Science Specialization by DeepLearning.AI & Amazon Web Services

Production settings may not have the same requirements as development environments. Moving data science and machine learning initiatives from concept to implementation necessitates cutting-edge expertise. Your projects must be designed and implemented for scalability and operational efficiency. Data science is an interdisciplinary field that brings together domain expertise, mathematics, statistics, data visualization, and programming skills.

The Practical Data Science Specialization brings these fields together in the AWS cloud using purpose-built machine learning technologies. It teaches you how to use Amazon SageMaker to gain practical skills for deploying data science projects and overcoming problems at each stage of the ML workflow.

This Specialization is for data-focused engineers, scientists, and analysts who are acquainted with Python and SQL and want to learn how to construct, train, and deploy scalable, end-to-end machine learning pipelines in the AWS cloud, both automated and human-in-the-loop.

Each of the ten weeks includes a thorough lab created exclusively for this Specialization that provides hands-on exposure with cutting-edge natural language processing (NLP) and natural language understanding (NLU) algorithms, such as BERT and FastText utilizing Amazon SageMaker.

This course offers:

• Flexible Schedule: Set and maintain flexible deadlines.
  
• Certificate : Earn a Certificate upon completion
• 100% online
  
• Advanced Level
  
• Approx. 3 months to complete: Suggested pace of 5 hours/week
  
• Subtitles: English

Coursera Rating: 4.6/5
Enroll here:https://www.coursera.org/specializations/practical-data-science