Azure Data Scientist Certification Training in Gurgaon
Master Azure Cloud and get prepared for Azure official certifications with our role based courses tailored to your specific needs
- Enroll for Cloud Architecture, Developer, Operations, DevOps, AI / ML, Networking and Security Certifications
- Experience blended learning through interactive offline and online sessions.
- Job Assured Course
Certification aligned to
- Course Duration - 2 months
- Get Trained from Industry Experts
Train using realtime course materials using online portals & trainer experience to get a personalized teaching experience.
Active interaction in sessions guided by leading professionals from the industry
Gain professionals insights through leading industry experts across domains
Enhance your career with 42+ in-demand skills and 20+ services
Azure Data Scientist Certification Overview
This Azure live-learning courses cover deep into designing, developing, deploying, and managing scalable solutions and infrastructure across AZURE platforms, equipping you for success in today’s fast-evolving technology landscape
- Benefit from ongoing access to all self-paced videos and archived session recordings
- Success Aimers supports you in gaining visibility among leading employers
- Get prepared for 10+ Azure official certifications with our role based courses tailored to your specific needs
- Engage with real-world capstone projects
- Engage in live virtual classes led by industry experts, complemented by hands-on projects
- Learn 42+ In-Demand Skills & 20+ Services
- Job interview rehearsal sessions
Basic, high-level knowledge of Azure Cloud services and terminology. Ideal starting point for Azure Certification for those with no prior IT/cloud experience transitioning to cloud careers, or business professionals seeking foundational cloud literacy
Familiarity with artificial intelligence (AI), machine learning (ML), and generative AI fundamentals and real-world applications
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What is Azure Certified Data Scientist ?
Azure Certified Data Scientist are essential for driving AI innovation in software development and testing. They manage the full deployment lifecycle—deploying apps, building and maintaining pipelines for web applications and K8s workflows, and automating development and testing processes. By streamlining workflows and resolving challenges in webapp deployment on cloud, and maintenance, they help organizations deliver reliable, high-performance applications faster and more efficiently.
The role of Azure Certified Data Scientist?
Azure Certified Data Scientist in software development and testing oversees the end-to-end lifecycle of web applications, from development to deployment and system performance optimization. Key responsibilities include:
Exploring Emerging Technologies: Leveraging Cloud technologies, Cloud networking, and security techniques to enhance efficiency and streamline deployment workflows.
Scalable Data, AI & WebApps Development: Designing and implementing web applications that address critical business needs.
Seamless Deployment: Coordinating web deployment with infrastructure management for smooth delivery.
Workflow Optimization: Creating, analyzing, and refining automation scripts and deployment workflows to maximize productivity.
For professionals aspiring to excel in this field, the Success Aimers Azure Certified Data Scientist Course provides hands-on training to master these skills. The program equips you to confidently manage deployment lifecycles, deployment pipelines, automation, and deployment processes, positioning you as a high-impact Azure Certified Cloud Engineers engineer in software development and testing.”**
Who should take this Azure Certified Data Scientist ourse?
The AWS Certified Cloud Engineer Course is tailored for professionals aiming to accelerate their careers in Cloud, data, and technology-driven sectors. It is particularly valuable for roles including:
Cloud Team Leaders
Software and DevOps Developers
Cloud Engineers and IT Managers
Cloud & Infrastructure Engineers
Cloud Researchers and Application Engineers
This program equips participants with the skills to lead DevOps & infrastructure initiatives, implement advanced deployment workflows, and drive innovation in software development and testing.
What are the prerequisites of Azure Certified Cloud Engineer Course?
Prerequisites for the Azure Certified Data Scientist Certification Course”
To ensure a seamless learning experience, candidates are expected to have:
Educational Background:Â An undergraduate degree or high school diploma in a relevant field.
Technical Foundation: Knowledge of IT, software development, or data science fundamentals.
Programming Skills:Â Basic proficiency in languages such as Python or JavaScript.
Cloud Familiarity:Â Experience with cloud platforms like AWS or Microsoft Azure.
Meeting these prerequisites enables learners to effectively grasp advanced Cloud concepts, including DevOps tool, pipeline workflows, Webapp deployment, and automation throughout the course.
What are the prerequisites of Azure Certified Data Scientist Course?
- Azure Certified Cloud Engineer
- SRE Reliability Engineer
- Cloud Solutions Release Manager
- Infrastructure/Cloud Automation Engineer
- Cloud Engineer / Cloud Architect
- Cloud Infrastructure Engineer
- Cloud Deployment Engineer
- Â
| Training Options | Weekdays (Mon-Fri) | Weekends (Sat-Sun) | Fast Track |
|---|---|---|---|
| Duration of Course | 3 months | 4 months | 1 month |
| Hours / day | 1-2 hours | 2-3 hours | 5 hours |
| Mode of Training | Offline / Online | Offline / Online | Offline / Online |
Azure Data Scientist Course Overview
This Azure Data Scientist Certification training enhances your career after choosing the relevant certification path based on the roles. You can practice with hands-on labs and capstone projects and gain proficiency with Azure tools. After completion of the course, you can leverage Job assistance services and enhance career prospects.
Below are the leading cloud career roles and the corresponding Azure certification path. You can choose the role(s) that progress your Azure certification journey toward your goals. These learning paths are recommendations, not requirements.
Data Science
Microsoft Azure Data Scientist Associate Course (DP-100)
Basics of Machine Learning
- Why Machine Learning is the Future?
- What is Machine Learning?
- Understanding various aspects of data - Type, Variables, Category
- Common Machine Learning Terms - Probability, Mean, Mode, Median, Range
- Types of Machine Learning Models - Classification, Regression, Clustering etc
- Basics of Machine Learning
Getting Started with Azure ML
- What is Azure ML and high-level architecture.
- Azure ML Experiment Workflow
- Azure ML Cheat Sheet for Model Selection
DP-100 – SetUp Azure Machine Learning Workspace
- Understand the AzureMLService Architecture
- Create the AzureML Workspace
- View and Manage Workspace Settings
- Overview of New AzureML Studio
- What is AzureML Datastore and Dataset?
- Create and Register a Datastore
- Create a Dataset
- Explore the AzureML Dataset
- Understanding the AzureML Compute Resources
- Create a Compute Cluster and Compute Instance
DP-100 – Run Experiments and Train Models
- What is an AzureML Pipeline?
- Create a Pipeline using AzureML Designer
- Submit the Designer Pipeline run
DP-100 – Deploy and consume the models
- Create an Inference Pipeline
- Deploy a real-time endpoint using Designer
- Create a batch inference pipeline using Designer
- Run a Batch Inference Pipeline from Designer
Data Processing using AzureML Designer
- Get Data to the workspace
- Import Data to the workspace from external sources
- Edit Metadata - Column Names
- Understanding the Run
- Edit Metadata - Data Type
- Export Data to the Blob Storage
- Add Columns to the Dataset
- Add Rows to the Dataset
- Normalization of Data Part 1
- Normalization of Data Part 2
- Clean Missing Data
- Partition and Sample Data Part 1
- Partition and Sample Data Part 2
Classification
- What is Logistic Regression
- Two Class Logistic Regression - Problem Statement
- Data Preparation for Two Class Classification
- Train the Model for Logistic Regression
- Evaluate the Model Part 1
- Evaluate the Model - Confusion Matrix
- Evaluate the Model - AUC ROC
- Parameters of Two Class Logistics Regression
- What is Decision Tree?
- Ensemble Learning in Decision Tree
- Bagging and Boosting in Decision Tree
- Hands On - Train the Two Class Boosted Decision Tree
- Evaluate and Compare Decision Tree output
Regression using AzureML Designer
- What is Linear Regression?
- Ordinary Least Square and Common Errors
- Hands On - Automobile Price Predictions Data Analysis
- Hands On - Automobile Price Predictions Data Processing
- Hands On - Automobile Price Predictions Train Model
- Hands On - Automobile Price Predictions Evaluate
- R-Squared or Coefficient of Determination
- Math Behind Gradient Descent
- Gradient Descent Explained
- Online or Stochastic Gradient Descent
- Experiment - Linear Regression using Online Gradient Descent
- Evaluate Linear Regression using Online Gradient Descent
Designer/Classic Studio vs Pandas and Scikit-Learn
- Pandas - Import Data for Experiments
- Pandas - Import Data Part 2
- Select Columns using Pandas
- Select Columns By drop method
- Add columns and rows
- Clean Missing Data
- Edit Metadata of columns using Pandas
- Create Summary Statistics using describe
- Clip Values - Remove Outliers using Constants
- Clip Values - Remove Outliers with Percentiles
- Convert and save a delimited file using Pandas
- Data Normalization
- Label Encoding of String Categorical data
- Why Hot encoding is required?
- Hot Encoding using Pandas get_dummies
- Split The Data for training and testing
- Build Logistic Regression using Python - Part 1
- Build Logistic Regression using Python - Part 2
Azure Machine Learning with AzureML SDK
- Introduction to AzureML SDK
DP-100 – SetUp Azure Machine Learning Workspace
- Create AzureML Workspace using SDK
- Verify the Workspace and Write the Workspace Config File
- Create and Register a Datastore using AzureML SDK
- Create and Register a Dataset using SDK
- Access Workspace, Datastore and Datasets using SDK
- Pandas DataFrame and AzureML Dataset conversions
- Upload local data to storage account via datastore
DP-100 – Run Experiments and Train Models
- Problem Statement - Run a sample experiment and log values
- Run a sample experiment using AzureML SDK - Part 1
- Run a sample experiment using AzureML SDK - Part 2
- Run a script in AzureML environment - Part 1
- Run a script in AzureML environment - Part 2
- Run a script in AzureML environment - Part 3
- Run a script in AzureML environment - Part 4
- Run a script in AzureML environment - Part 5
- Train and Run a Model Script in AzureML Part 1
- Train and Run a Model Script in AzureML Part 2
- Train and Run a Model Script in AzureML Part 3
- Train and Run a Model Script in AzureML Part 4
- Train and Run a Model Script in AzureML Part 5
- Provisioning Compute Cluster using SDK
- Automate Model Training using AzureML SDK
- Automate Model Training - Define Pipeline Steps
- Automate Model Training - Define Run Configuration
- Automate Model Training - Define Build and Run
- Detour - Command Line Arguments
- Automate Model Training - Create Dataprep Step
- Automate Model Training - Create Training Step
- Run the pipeline and see the results
Using Python Scripts in AzureML Designer
- Simple Python Script in Designer
- Execute Python Script using Zip Bundle
- Execute Python Script using Zip Bundle - Hands on
Use Automated ML to create Optimal Models
- What is Azure AutoML?
- Use the Automated ML interface in Azure Machine Learning studio
- View the AutoML Run Result
- Note on Normalized Macro Recall
- Use Automated ML from the Azure Machine Learning SDK
- Retrieve the Best Model and View results
Use Azure Hyperdrive to Tune Hyperparameters
- Introduction to Azure Hyperdrive
- Define the Hyperparameter Search Space
- Select a Sampling method
- Define Early Termination Options
- Configure the Hyperdrive run
- Create the Training Script for Hyperdrive run
- Retrieve the Best Model
Use model explainers to interpret models
- Evaluating MIs and VMs based on specific requirements
- configure Azure SQL Managed Instance for scale and performance
- More about Azure SQL Managed Instance
- Accessing Azure SQL Managed Instance in SSMS
- Implement Azure SQL Managed Instance database copy and move
- configure SQL Server in Azure VMs - Part 1
- configure SQL Server in Azure VMs - Part 2
- Logging into SQL Server on Azure Virtual Machines
Configure database authentication and filegroups
- create users from Azure AD identities (MIs and VMs)
- manage certificates using T-SQL
- configure database and object-level permissions using GUI
- configure security principals (MIs and VMs)
- recommend table, index storage inc. filegroups (MI and VMs)
Evaluate and implement an alert and notification strategy
- create event notifications based on metrics
- configure notifications for task success/failure/non-completion
- manage schedules and automate maintenance jobs
- create alerts for server configuration changes
- split and filter event notifications for Azure resources
Identify performance-related tasks
- determine sources for performance metrics
- implement index maintenance tasks (Database Engine Tuning Advisor)
- Monitor activity: SQL Profile, Extended Events, Performance Dashboard
- configure Resource Governor for performance (VM/MI)
Create scheduled tasks
- apply patches and updates for hybrid and IaaS deployment
- implement Azure Key Vault and disk encryption for Azure VMs
- configure multi-server automation
- implement policies by using automated evaluation modes
Perform backup and restore a database by using database tools – VM’s
- automate backups
- perform a database backup with options
- database (and transaction log) backups with options
- perform a database restore with options
- perform restore of user databases in T-SQL
- backup and restore to and from cloud storage
Recommend and test HA/DR strategies, and configure HA/DR
- configure replication - Transactional replication
- evaluate HADR for hybrid and Azure-specific deployments
- Creating Virtual Machines for Failover Cluster and Always on Availability Group
- Connecting Virtual Machines to a Domain
- Configure failover cluster instances on Azure VMs
- Checking SQL Server Installation and preparing for AO
- configure quorum options for a Windows Server Failover Cluster
- create an Availability Group
- Failover, integrate database into Always on Availability Group
- configure an Always on Availability Group listener
- Log shipping theory and creating folders
- Configure log shipping
- Testing log shipping and troubleshooting
Hours of content
Live Sessions
Software Tools
After completion of this training program you will be able to launch your carrer in the world of AI being certified as Microsoft Certified Azure Fundamentals – Exam AZ-900, Microsoft Certified Azure AI Fundamentals – Exam AI -900 & Microsoft Certified Azure Data Fundamentals – Exam DP -900 course.
With the Microsoft Certified Azure Fundamentals – Exam AZ-900, Microsoft Certified Azure AI Fundamentals – Exam AI -900 & Microsoft Certified Azure Data Fundamentals – Exam DP -900 course in-hand you can boost your profile on Linked, Meta, Twitter & other platform to boost your visibility
- Get your certificate upon successful completion of the course.
- Certificates for each course
- Azure BLOB Storage
- AWS Polly
- Azure Databricks
- Azure SQL Server
- Azure Functions
- Azure App Services
- Azure Logic Apps
- Azure Document DB
- Azure Fabric
- Azure Kubernetes Service (AKS)
- Azure Container Registry (ACR)
- API Management
- Azure Search
- Azure Moniter
45% - 100%
Designed to provide guidance on current interview practices, personality development, soft skills enhancement, and HR-related questions
Receive expert assistance from our placement team to craft your resume and optimize your Job Profile. Learn effective strategies to capture the attention of HR professionals and maximize your chances of getting shortlisted.
Engage in mock interview sessions led by our industry experts to receive continuous, detailed feedback along with a customized improvement plan. Our dedicated support will help refine your skills until your desired job in the industry.
Join interactive sessions with industry professionals to understand the key skills companies seek. Practice solving interview question worksheets designed to improve your readiness and boost your chances of success in interviews
Build meaningful relationships with key decision-makers and open doors to exciting job prospects in Product and Service based partner
Your path to job placement starts immediately after you finish the course with guaranteed interview calls
Why should you choose to pursue a Microsoft Certified Azure Fundamentals – Exam AZ-900, Microsoft Certified Azure AI Fundamentals – Exam AI -900 & Microsoft Certified Azure Data Fundamentals – Exam DP -900 Course with Success Aimers?
Success Aimers teaching strategy follow a methodology where in we believe in realtime job scenarios that covers industry use-cases & this will help in building the carrer in the field of Azure & also delivers training with help of leading industry experts that helps students to confidently answers questions confidently & excel projects as well while working in a real-world
What is the time frame to become competent as a Azure Engineer?
To become a successful AWS Engineer required 1-2 years of consistent learning with dedicated 3-4 hours on daily basis.
But with Success Aimers with the help of leading industry experts & specialized trainers you able to achieve that degree of mastery in 6 months or one year or so and it’s because our curriculum & labs we had formed with hands-on projects.
Will skipping a session prevent me from completing the course?
Missing a live session doesn’t impact your training because we have the live recorded session that’s students can refer later.
What industries lead in Azure implementation?
Manufacturing
Financial Services
Healthcare
E-commerce
Telecommunications
BFSI (Banking, Finance & Insurance)
“Travel Industry
Does Success Aimers offer corporate training solutions?
At Success Aimers, we have tied up with 500 + Corporate Partners to support their talent development through online training. Our corporate training programme delivers training based on industry use-cases & focused on ever-evolving tech space.
How is the Success Aimers Microsoft Certified Azure Fundamentals – Exam AZ-900, Microsoft Certified Azure AI Fundamentals – Exam AI -900 & Microsoft Certified Azure Data Fundamentals – Exam DP -900 Course reviewed by learners?
Our Azure Cloud Engineer Course features a well-designed curriculum frameworks focused on delivering training based on industry needs & aligned on ever-changing evolving needs of today’s workforce due to Cloud Computing (AWS)
Also our training curriculum has been reviewed by alumi & praises the thorough content & real along practical use-cases that we covered during the training. Our program helps working professionals to upgrade their skills & help them grow further in their roles…
Can I attend a demo session before I enroll?
Yes, we offer one-to-one discussion before the training and also schedule one demo session to have a gist of trainer teaching style & also the students have questions around training
programme placements & job growth after training completion.
What batch size do you consider for the course?
On an average we keep 5-10 students in a batch to have a interactive session & this way trainer can focus on each individual instead of having a large group
Do you offer learning content as part of the program?
Students are provided with training content wherein the trainer share the Code Snippets, PPT Materials along with recordings of all the batches
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