The world of data science is ever-expanding, as more and more data is collected in an effort to help businesses improve. The Microsoft Data Scientist Certification can allow you to get your foot in the door of this lucrative career path.
In recent years, data science has become a big business. It is used to help businesses become more efficient as well as learn about their clients and improve productivity.
Data science can turn a business around or allow a small startup to grow into a company fast. Because of this, many IT professionals are turning to certification to help them in their career progression as data scientists.
Let’s take a deeper look at the data scientist certification offered by Microsoft and also discuss accreditation.
Microsoft Certified: Azure Data Scientist
One of Microsoft’s top data science certifications is the Azure Data Scientist certification. This is an associate-level certification that sits in the middle of the data science certification tree. Often times, you can participate in an associate-level certification with no other Microsoft certifications needed, though it is always worth checking at the time you choose to become certified if this is the case.
If you are new to the world of data science, you may be better off taking the fundamental certification instead entitled “Microsoft Certified Azure Fundamentals,” as this is an entry-level certification as opposed to the data scientist certification, which is an intermediate level.
If you’re looking to reach the pinnacle of Microsoft’s data science certifications, then you’ll need to take a relevant associate course, such as the Azure Data Scientist before you qualify to progress to these expert-level courses: Microsoft Certified: Azure DevOps Engineer or Microsoft Certified: Azure Solutions Architect.
Exams and Modules
To become a Microsoft Certified Azure Data Scientist, you’ll need to take and pass the DP-100 exam entitled “Designing and Implementing a Data Science Solution on Azure.” This exam is available in four languages: English, Korean, Chinese, and Japanese. It will test participants on their understanding and ability to define and prepare development environments, prepare data for modeling, as well as perform feature engineering and model development.
To fully train for the exam and gain the knowledge an Azure Data Scientist should possess, participants need to study the following skills: development environment, data for modeling, feature engineering and develop models.
These overarching skills are broken down into a variety of modules in which participants can study online or as part of a training course. The models which should be studied before undertaking the exam are as follows:
Explore AI Solution Development with Data Science Services in Azure
- Introduction to Data Science in Azure
- Choose the Data Science service in Azure you need
Build AI Solutions with Azure Machine Learning Service
- Introduction to Azure Machine Learning service
- Train a local ML model
- Register and deploy ML models
- Automate the ML model selection
Get Started with Machine Learning with an Azure Data Science Virtual Machine
- Introduction to the Azure Data Science Virtual Machine
- Explore the types of Azure Data Science
- Provision and use an Azure Data Science
Perform Data Engineering with Azure Databricks
- Introduction to Azure Databricks (AD)
- Access SQL Data Warehouse instances with AD
- Data ingestion with Azure Data Factory
- Read and write data
- Perform basic data transformations
- Perform advanced data transformation
- Create data pipelines by using Databricks Delta
- Work with streaming data
- Create data visualizations by using Azure Databricks and Power BI
Extract Knowledge and Insights from your Data with Azure Databricks
- Introduction to AD
- Read and write data
- Perform exploratory data analysis
- Train, evaluate, and select machine-learning models
- Deep learning
- Perform text analytics
Introduction to Machine Learning with Python and Azure Notebooks
- Analyze climate data with Azure Notebooks
- Predict flight delays by creating a machine learning model in Python
- Analyze the sentiment of reviews with Keras
When you become a Microsoft Certified: Azure Data Scientist, you can officially call yourself a data scientist and would qualify for data scientist roles such as a data scientist, data analyst, data & applied scientist, delivery data scientist, as well as qualifying to undertake expert-level Microsoft certifications.
Getting certified not only increases your job search and hire-ability, but it is also likely to increase your potential salary too.
Many budding data scientists opt to take a combo certification course to maximize their time and also their learning.
The most common combo-course is the MCA Microsoft Azure Data Scientist w/ MCA Microsoft Azure Data Engineer. This allows participants to figuratively kill two birds with one stone when it comes to certification, allowing them to learn data scientist skills alongside those required by a data engineer.
Because this is a combination of two courses, there will be much more to learn and an extra exam to boot, meaning that this type of certification option is best delivered as part of a group training course.
Not to worry if you can’t leave your place of work, however, as most reputable certification agencies will offer both on-campus and off-campus training options, allowing you to learn in the way that best suits you.
Data science is big business, and if you are looking for a slice of the pie, certification is your best route to the table. While the initial financial outlay may seem daunting, it is important to remember that you are investing in yourself and your future.
And remember that training companies, as well as Microsoft themselves, are there to help you along your journey to your dream career.