Certified Data Science Professional
Subjects
The Certified Data Science Professional course is made up of four Certifications, provided through Microsoft. Each Certification is comprised of numerous courses:
Microsoft Azure Data Fundamentals
In this course you will learn the fundamentals of database concepts in a cloud environment, get basic skilling in cloud data services, and build your foundational knowledge of cloud data services within Microsoft Azure.
Microsoft Azure Fundamentals
This course will provide foundational knowledge on cloud concepts; core Azure services; security, privacy, compliance and trust; and Azure pricing and support.
Microsoft Azure AI Fundamentals
This course introduces fundamentals concepts related to AI, and the services in Microsoft Azure that can be used to create AI solutions.
Microsoft Azure Data Science Associate
With this course you will learn how to use Azure services to develop, train, and deploy machine learning solutions.
Other Course Inclusions
Microsoft Learn Content
- Open Source Software (SQL, Python, R, Hadoop)
- Job ready personal development skills
- Capstone project – undertake a live data challenge to build a capstone project for your portfolio to demonstrate world skills to hirers
This course will provide foundational knowledge on cloud concepts; core Azure services; security, privacy, compliance and trust; and Azure pricing and support.
- Define cloud computing and its key advantages
- Explain public, private, and hybrid cloud models
- Identify core Azure architectural components, such as regions, geographies, and resource groups
- Identify usage cases for Azure core services and products, such as virtual machines and storage
- Describe virtual network security connectivity options such as Network Security Groups
- Describe Azure identity authentication and authorization options
- Describe privacy, compliance, and data protection standards
- Use an Azure subscription
- Plan and manage costs
This course introduces fundamentals concepts related to AI, and the services in
Microsoft Azure that can be used to create AI solutions.
- Describe AI workloads and considerations
- Describe fundamental principles of machine learning on Azure
- Describe features of computer vision workloads on Azure
- Describe features of Natural Language Processing (NLP) workloads on Azure
- Describe features of conversational AI workloads on Azure
With this course you will learn how to use Azure services to develop, train, and deploy machine learning solutions.
- Know-how Azure services can support and augment the data science process
- Use Azure Machine Learning service to automate the data science process end to end
- Know about the machine learning pipeline and how the Azure Machine Learning service’s AutoML and HyperDrive can automate some of the laborious parts of it
- Automatically manage and monitor machine learning models in the Azure Machine Learning service
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