Microsoft Azure Data Scientist DP-100 FAQ

In this blog, we have answered some of the most frequently asked questions (DP-100 FAQ) to us in our FREE class of Azure Data Scientist Associate [DP-100].

Azure Data Engineer

An Azure Data Engineer is a professional responsible for designing, implementing, and managing data solutions on the Azure cloud platform. They specialize in data ingestion, transformation, storage, and analysis using tools like Azure Data Factory, Azure Synapse Analytics, and Azure Databricks. By leveraging Azure’s services, they ensure data pipelines are efficient, scalable, and secure, enabling organizations to make data-driven decisions. Azure Data Engineers also work with big data, machine learning integration, and real-time analytics to create innovative solutions tailored to business needs.

Azure Data Scientist Salary

The salary for an Azure Data Scientist varies depending on experience, location, and industry. In the United States, entry-level positions typically range from $90,000 to $120,000 annually. Mid-level professionals earn around $120,000 to $150,000, while senior-level roles can exceed $180,000. Globally, salaries may differ, with markets like the UK and Canada offering competitive packages. Factors such as certifications in Azure Machine Learning, AI, or Data Science, and hands-on expertise in predictive analytics, contribute to higher earnings. Azure Data Scientists are in high demand as businesses embrace cloud-based AI solutions.

Azure Data Scientist Jobs

Azure Data Scientist jobs are in high demand, offering opportunities to work with cutting-edge AI and machine learning tools on Microsoft’s Azure platform. These roles typically involve designing predictive models, analyzing complex datasets, and deploying AI solutions using services like Azure Machine Learning, Azure Databricks, and Cognitive Services. Professionals in this field often require skills in Python, R, SQL, and a deep understanding of data science workflows. With Azure’s enterprise-ready solutions, data scientists can drive impactful decisions, making it a top choice for businesses across industries.

Do you also have such questions in mind or are confused about the DP-100 Microsoft Azure Data Scientist Associate certification?

1. What is the difference between Data Science and Data Engineering?
2. How is Data Science different from Azure Data Science?
3. Is python required to prepare for DP-100 certification?

Then you have landed at the correct place my friend!

Also, Do Read: Our Blog Post On Convolution Neural Network.

Azure Data Scientist DP-100 FAQ (Commonly Asked Questions)

Q1)  What is Azure?

Answer:  Azure is a cloud computing platform and an online portal that allows access and manage the cloud services and resources provided by Microsoft. The services and resources include storing data and transforming it, depending on user requirements.

Check Out: AWS Sagemaker Pricing. Click here

Q2) What is the major difference between a Data Scientist and an Azure Data Scientist?

Answer: This is one of the most frequently asked DP-100 FAQs in our free class. A data scientist applies machine learning techniques to train, evaluate, and deploy models that can solve business problems whereas an Azure Data Scientist applies its knowledge of data science and machine learning to implement and run machine learning workloads on Azure by using the Azure Machine Learning Service.

Do Check:  What is the difference in Data Science vs Data Analytics vs Data Engineer.

Q3) How is Artificial Intelligence (AI) different from Machine Learning (ML)?

Answer: AI and ML are two very common buzzwords in today’s time that are often used interchangeably. Artificial Intelligence is the mechanism to incorporate human intelligence into machines through a set of rules also known as algorithms. The word Artificial Intelligence is made of two words: “Artificial” meaning something made by humans or non-natural things and “Intelligence” meaning the ability to understand or think accordingly.

On the other hand, machine learning is a subset of an application of AI that provides the system with the ability to automatically learn and improve from experience without being explicitly programmed.

Also, Read Our Blog Post On Hyperparameter.

To know more about AI and ML in detail you can read our blog Introduction To Data Science and Machine Learning

Q4) What is the difference between Data Science and Data Engineering?

Answer: This is one of the most frequently asked questions and the most confusing one also. There is a significant overlap between data engineers and data scientists when it comes to skills and responsibilities and the main difference key point is the focus area of both these professions.

Note: Do Check Our Blog Post On Azure Machine Learning

Also Checkout: Our Blog Post on the Azure machine learning model.

Data Science refers to using Scientific methods to turn data into some value that can be used in predictive modeling. It combines different fields of work in statistics and computation to interpret data for decision-making.

Data Engineering is a form of data science that targets practical applications of data collection and analysis which includes storing data, receiving data, transforming data, and making it available for the end-users.

Note:  Read Our Blog Post on  DP-900 vs DP-100 vs DP-200 vs DP-201

Q5) What is the difference between the DP100 exam and the AI900 exam?

Answer: AI-900 Azure AI Fundamentals certification is a fundamental level certification of Microsoft Azure. It is ideal for aspiring cloud professionals to capture fundamental knowledge in machine learning and AI concepts and want to start their career in Artificial Intelligence, Machine Learning, or Data Science. It is generally used to prepare for other Azure role-based certifications such as Azure Data Scientist Associate [DP-100].

To know more about the AI-900 certification read our blog [AI-900] Microsoft Certified Azure AI Fundamentals Course: Everything you must know.

DP-100 Azure Data Science certification is an associate-level certification for those who apply their knowledge of data science and machine learning to implement and run machine learning workloads on Azure.

To know more about the DP-100 certification read our blog DP 100 Microsoft Certified Azure Data Scientist Associate.

Q6) What is the level of Python required for the DP-100 certification?

Answer: Since DP-100 is a data science certification and Python is the most widely used and recommended language to work within the data science and machine learning field. So yes if you have basic knowledge of python, commands, libraries, etc it will help in a better understanding of code and concepts of the certification else you can always learn on the way.

Note: Do Check Our Blog Post  On MLOps For An Overview.

Q7) What level of mathematical and statistical knowledge we need to have as a prerequisite for the DP-100 certification?

Answer: Basic level of mathematics and statistical concepts knowledge will help in a better understanding of the machine learning model’s evaluation metrics and outcomes.

Q8) How does  Data Science differ from Business Intelligence?

Answer: Data science deals with predictive analysis and prescriptive analysis (i.e., What will happen?), while BI deals with descriptive analysis (i.e., What has happened?). Both of them involve the use of data but are totally different from one another as both have different tools, responsibilities, and domains to focus on.

To Know More About Microsoft Azure Object Detection. Click Here

Q9) What is the difference between Azure ML Classic Studio and Azure ML Studio and which one is the best?

Answer: Azure ML Classic Studio was the first drag and drop tool which was a standalone service that offered visual experience but however, it does not interoperate with Azure Machine learning. It was released in 2015. It does not support Code SDKs, ML pipeline, Automated model training and has a basic model for MLOPs and many other features were missing that are now a part of Azure Machine Learning Studio.

So Azure ML Studio is a much better choice to use to train and deploy machine learning models and perform other operations on it and also DP-100 course is designed on Azure ML Studio.

To know more about Azure ML Studio you can read our blog Azure Machine Learning Studio & Its Features.

Q10) What is docker and is it covered in Implementing an Azure Data Science Solution  DP-100 course?

Answer: Docker is an open-source platform that is based on Linux containers for developing and running applications inside containers. It is not related to the DP-100 course.

To know more about Docker and its architecture you can read our blog Docker Architecture: A Complete Docker Introduction

Q11) What is the difference between Jupyter Notebook and JupyterLab? 

Answer:  Jupyter Notebook is a web-based interactive computational environment for creating Jupyter notebook documents that supports several languages like Python, R, etc., and is largely used for data analysis, data visualization, and more.

JupyterLab is the next-generation user interface including notebooks. It has a modular structure, where you can open several notebooks or files (e.g. HTML, Text, etc) as tabs in the same window. It offers more of an IDE-like experience.

Hope this article clears your doubt regarding the DP-100 certification!

Also check: How to create a Load Balancer in Azure using the Azure Portal.

FAQs

Related/References:

• Join Our Generative AI Whatsapp Community
• Azure AI/ML Certifications: Everything You Need to Know
• Azure GenAI/ML : Step-by-Step Activity Guide (Hands-on Lab) & Project Work
• [DP-100] Microsoft Certified Azure Data Scientist Associate: Everything you must know
• Microsoft Certified Azure Data Scientist Associate | DP 100 | Step By Step Activity Guides (Hands-On Labs)
• [AI-900] Microsoft Certified Azure AI Fundamentals Course: Everything you must know
• Azure Machine Learning Service Workflow: Overview for Beginners
• Azure ML Model
• Automated ML In Azure
• Data Science VS Data Analytics VS Data Engineer
• Azure Free Account: Steps to Register for Free Trial Account

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