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Azure Data Engineering Certification Training (DP-203)
About This Course
Kickstart a High-Growth Data Engineering Career
Are you ready to take your career to the next level? Our Azure Data Engineering Certification Training (DP-203) is designed for professionals looking to break into or advance in the rapidly expanding field of data engineering.
Why Choose Our Azure Data Engineering Training?
Ace the DP-203 Exam with Confidence
This comprehensive training program is aligned with the official DP-203: Data Engineering on Microsoft Azure certification exam. Our expert instructors will guide you through all the key concepts, tools, and techniques you’ll need to pass the exam and earn your certification.
Unlock High-Demand Career Opportunities
With cloud computing and data engineering skills in high demand, this course opens doors to new roles and lucrative career paths. Whether you’re looking to transition into a data engineering role or enhance your existing skills, this certification is a valuable asset.
Hands-on Learning with Practical Sessions
Our training isn’t just theory! We offer a balanced mix of classroom learning and hands-on practical sessions, ensuring that you can immediately apply what you’ve learned in real-world scenarios. You’ll work with Azure tools and services, including Azure Data Lake, SQL Database, Databricks, and more.
What You’ll Learn
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Design and Implement Data Storage Solutions
Learn how to design and implement scalable, secure data storage solutions using Azure Storage services and Azure Data Lake Storage. -
Manage and Develop Data Processing Solutions
Master the tools and techniques to implement batch processing, stream processing, and orchestrate data workflows with Azure Data Factory and Azure Databricks. -
Secure and Monitor Data Solutions
Understand how to implement security best practices for data solutions on Azure, including data encryption, access control, and compliance standards. -
Integrate Data Solutions into Azure
Learn how to integrate on-premises data systems with Azure and create seamless end-to-end data pipelines using Azure Synapse Analytics and other tools.Course Features
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Expert-Led Training
Learn from certified instructors with real-world experience in Azure Data Engineering. -
Flexible Learning Options
Choose between in-person or online sessions, with flexible timings to suit your schedule. -
Comprehensive Study Materials
Get access to a wide range of learning resources, including study guides, practice tests, and reference materials. -
Post-Course Support
Receive continued support from our team after the course ends, helping you with job placements, exam preparation, and career advice.
Placement Solutions for IT Professionals
We don’t just train you — we help you secure your dream job! Our placement services are designed to assist you in finding the right role and launching your career in data engineering.
We work closely with top companies to connect our graduates with high-paying opportunities in the tech industry.
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Learning Objectives
Industry-Specific Skills:
Develop expertise in solving complex data engineering challenges specific to banking, retail, and healthcare sectors.
Real-World Application:
Gain practical experience in building and deploying real-time data pipelines that provide valuable insights and automation in business-critical processes.
Hands-On Projects:
Complete two full projects that simulate real-life scenarios, showcasing your ability to design, build, and implement data solutions that meet the needs of modern enterprises.
Certification-Ready Skills:
By the end of this module, you will be ready to tackle the DP-203 exam and demonstrate your ability to apply your knowledge in real-world, industry-specific contexts.
Project Deliverables:
End-to-End Data Pipelines for each project.
Machine Learning Models for fraud detection, marketing insights, and patient outcome predictions.
Dashboards and Reports for real-time monitoring and decision-making.
Documentation for each project, including design documents, code snippets, and explanations of the workflow.
Material Includes
- Comprehensive Courseware and Study Guides
- Detailed, easy-to-follow course materials that cover all exam objectives for the DP-203 exam. Includes step-by-step instructions, diagrams, and examples of key concepts.
- Hands-On Lab Exercises
- Access to real-world lab environments where you can practice working with Azure tools like Azure Data Factory, Databricks, Synapse Analytics, and more. These labs reinforce learning through practical application.
- Practice Tests and Quizzes
- A set of practice exams and quizzes to test your knowledge and readiness for the DP-203 certification exam. Detailed explanations are provided for correct and incorrect answers to enhance learning.
- Instructor-Led Video Sessions
- Access to recorded lectures and live sessions led by Azure-certified instructors. These videos break down complex concepts and demonstrate how to implement Azure solutions in real-world scenarios.
- Project Work and Case Studies
- Real-time industry-based projects that simulate challenges faced in sectors like banking, retail, and healthcare. These projects help you apply your skills to real-world data engineering problems.
- Post-Course Resources
- Ongoing support including access to additional reference materials, study aids, career guidance, resume-building assistance, and job placement support to help you secure your next role in data engineering.
Requirements
- Basic Knowledge of Programming and Databases
- A fundamental understanding of programming (preferably Python or SQL) and databases is recommended. Familiarity with relational databases and data manipulation techniques will help you grasp the core concepts more effectively.
- Azure Fundamentals
- Although not mandatory, it is beneficial to have prior knowledge of Azure fundamentals (such as Azure Virtual Machines, Networking, Storage, and Basic Cloud Concepts). You can take the Azure Fundamentals (AZ-900) course as a prerequisite to strengthen your foundation in Azure.
- Access to a Computer and Internet
- You will need a computer with internet access to participate in hands-on labs, access course materials, and attend live or recorded sessions. A minimum of 4 GB RAM and 2 GB of free disk space is recommended for smooth performance during labs and exercises.
- Commitment to Learning and Hands-On Practice
- Success in this training requires active participation in labs, projects, and practice exercises. It is important to allocate dedicated time each week to complete the hands-on tasks and study for the certification exam.
Target Audience
- Aspiring Data Engineers – Professionals looking to break into the data engineering field by gaining expertise in Azure and cloud-based data solutions.
- IT Professionals Seeking Career Advancement – Individuals already working in IT, data analysis, or software development, aiming to upgrade their skills and transition into data engineering roles.
- Cloud Enthusiasts – Learners who are passionate about cloud technologies and want to specialize in building scalable, secure data solutions on Microsoft Azure.
- Data Analysts and Data Scientists – Analysts and data scientists who want to deepen their understanding of data pipelines, processing, and engineering techniques to complement their analytical skills.
- Professionals in Banking, Retail, and Healthcare – Individuals from industries like finance, retail, or healthcare looking to develop industry-specific data engineering expertise for building data pipelines, predictive models, and advanced analytics solutions.
Curriculum
3 Lessons50h
Module 1: Introduction to Data Engineering on Azure
Overview of Data Engineering
Understanding the role of a data engineer
Key responsibilities and skill sets
Azure Fundamentals for Data Engineering
Introduction to Microsoft Azure
Overview of Azure Data Services and Ecosystem
Setting up an Azure account and navigating the portal
Introduction to the DP-203 Exam
Exam format and objectives
Study tips and resources
Module 2: Designing and Implementing Data Storage Solutions
Azure Storage Overview
Types of data storage in Azure
Choosing the right storage service based on requirements
Working with Azure Blob Storage
Setting up and managing Azure Blob Storage
Uploading, downloading, and managing blobs
Azure Data Lake Storage Gen2
Setting up Azure Data Lake
Implementing hierarchical namespaces
Managing access control and security
Azure SQL Database and Synapse Analytics
Implementing and managing relational databases
Introduction to Azure Synapse Analytics for big data
Hands-On Lab: Configuring and Managing Storage Solutions
Module 3: Data Processing and Transformation
Batch Data Processing
Understanding ETL (Extract, Transform, Load) processes
Using Azure Data Factory for batch processing
Stream Data Processing
Introduction to real-time data processing
Implementing Azure Stream Analytics
Stream data from IoT devices and other sources
Working with Azure Databricks
Introduction to Apache Spark in Azure
Setting up Databricks workspaces and clusters
Data processing and transformations with Spark
Hands-On Lab: Creating and Managing Data Pipelines
Module 4: Orchestrating Data Solutions with Azure Data Factory
Introduction to Azure Data Factory
Overview of Data Factory components
Understanding pipelines, datasets, and activities
Designing and Deploying Pipelines
Building ETL workflows using Data Factory
Scheduling and automating pipeline runs
Monitoring and Troubleshooting Pipelines
Tracking pipeline execution and monitoring performance
Handling errors and debugging failed runs
Integrating Data Factory with Other Azure Services
Using Data Factory with Azure Blob Storage, SQL Databases, and more
Hands-On Lab: Building and Automating Data Pipelines
Module 5: Data Security and Monitoring
Data Security Best Practices
Implementing encryption at rest and in transit
Managing authentication and authorization in Azure
Securing data with Azure Active Directory (AAD)
Managing Azure Security
Azure Key Vault for managing secrets
Role-Based Access Control (RBAC)
Implementing data security at scale
Monitoring Data Solutions
Using Azure Monitor and Log Analytics for performance monitoring
Configuring alerts and diagnostics
Hands-On Lab: Implementing Security Features and Monitoring
Module 6: Advanced Data Solutions and Integrations
Implementing Big Data Solutions with Azure Synapse Analytics
Data warehousing with Synapse Analytics
Querying large datasets with SQL on-demand and dedicated pools
Implementing Azure Machine Learning for Predictive Analytics
Introduction to Azure ML
Using data pipelines for training and deployment of machine learning models
Integrating with On-Premises Data Sources
Connecting on-premises databases with Azure services
Hybrid data solutions and migration strategies
Using Azure Event Grid and Azure Functions
Event-driven architecture in Azure
Serverless computing with Azure Functions
Hands-On Lab: Building Advanced Data Solutions with Synapse and Machine Learning
Module 7: Final Exam Preparation and Review
Review of Key Concepts and Exam Objectives
Recap of all exam objectives and critical concepts
Study strategies for the DP-203 exam
Practice Test and Mock Exam
Full-length practice test to assess readiness
Review of answers and explanations
Final Q&A and Exam Tips
Common mistakes to avoid
Exam-day strategies and tips
Post-Course Career Support and Resources
Resume building, interview preparation
Job search strategies and placement support
Module 8: Real-Time Projects in Data Engineering for Banking, Retail, and Healthcare
In this module, you’ll work on two real-time projects that involve building end-to-end data engineering solutions in three key industries: Banking, Retail, and Healthcare. These projects will help you develop a deeper understanding of how data engineering practices are applied in various sectors, allowing you to demonstrate your ability to work on complex, real-world data pipelines.
Your Instructors
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₹16,999.00₹35,699.00
Material Includes
- Comprehensive Courseware and Study Guides
- Detailed, easy-to-follow course materials that cover all exam objectives for the DP-203 exam. Includes step-by-step instructions, diagrams, and examples of key concepts.
- Hands-On Lab Exercises
- Access to real-world lab environments where you can practice working with Azure tools like Azure Data Factory, Databricks, Synapse Analytics, and more. These labs reinforce learning through practical application.
- Practice Tests and Quizzes
- A set of practice exams and quizzes to test your knowledge and readiness for the DP-203 certification exam. Detailed explanations are provided for correct and incorrect answers to enhance learning.
- Instructor-Led Video Sessions
- Access to recorded lectures and live sessions led by Azure-certified instructors. These videos break down complex concepts and demonstrate how to implement Azure solutions in real-world scenarios.
- Project Work and Case Studies
- Real-time industry-based projects that simulate challenges faced in sectors like banking, retail, and healthcare. These projects help you apply your skills to real-world data engineering problems.
- Post-Course Resources
- Ongoing support including access to additional reference materials, study aids, career guidance, resume-building assistance, and job placement support to help you secure your next role in data engineering.
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