Azure Data Engineering Master Program with AI, Databricks & Power BI – Live Training
(Master Azure Data Engineering with hands-on training in Azure Data Factory, Databricks, PySpark, Delta Lake, Synapse Analytics, and AI-powered development.)
Azure Data Engineering with AI is a comprehensive, hands-on training program designed to help you master modern data engineering using Microsoft Azure. Learn how to build scalable data pipelines, manage cloud storage, process large datasets with Azure Databricks and PySpark, implement Delta Lake and Medallion Architecture, and create enterprise reporting solutions using Azure Synapse Analytics.
This course combines industry best practices with real-time projects and practical labs covering Azure Data Factory (ADF), Azure Data Lake Storage Gen2 (ADLS Gen2), Blob Storage, ETL/ELT pipelines, data transformation, and workflow automation. You’ll also discover how to leverage AI tools like GitHub Copilot to generate SQL, PySpark code, ADF expressions, technical documentation, and accelerate debugging and code reviews.
By the end of the course, you’ll complete a real-world end-to-end capstone project, building a production-ready data pipeline from data ingestion to analytics and visualization using Azure Data Factory, ADLS Gen2, Azure Databricks, Delta Lake, Azure Synapse Analytics, and Power BI. This job-oriented program equips you with the practical skills, hands-on experience, and industry knowledge required to become a confident Azure Data Engineer.
Prerequisites:
- Basic SQL
- No Azure experience required
About the Instructor:
| Annapoorani is an experienced IT professional and passionate technical trainer with over 9+ years of diversified industry experience in software development, database technologies, and cloud-based data solutions. She has extensive knowledge of modern data engineering concepts and specializes in building scalable data pipelines, implementing ETL/ELT processes, and designing cloud-native data platforms using Microsoft Azure. Her expertise includes Azure Data Factory (ADF), Azure Data Lake Storage Gen2 (ADLS Gen2), Azure Databricks, PySpark, Delta Lake, Azure Synapse Analytics, Azure SQL Database, and Lakehouse Architecture, enabling organizations to develop efficient, secure, and high-performance data solutions.
With 4+ years of dedicated online training experience, Annapoorani has successfully trained students, software professionals, and career changers through structured, hands-on learning programs. Her teaching methodology focuses on bridging the gap between theory and real-world implementation by combining interactive sessions, practical assignments, live demonstrations, and industry-oriented projects. She believes in creating a strong foundation in data engineering while helping learners gain the confidence to work with enterprise-grade Azure technologies and modern data platforms. Annapoorani is committed to preparing learners for successful careers in Data Engineering by providing comprehensive guidance on industry best practices, real-time project development, interview preparation, and problem-solving techniques. Her practical approach, clear explanations, and focus on current industry trends ensure that students not only understand the concepts but also develop the skills required to excel in today’s cloud and data-driven ecosystem. Her goal is to empower every learner with the knowledge and confidence needed to become a job-ready Azure Data Engineer. |
Live Sessions Price:
For LIVE sessions – Offer price after discount is 300 USD 259 119 USD Or USD13000 INR 12900 INR 9900 Rupees
OR
Free Demo Session:
1st September @ 8 PM – 9 PM (IST) (Indian Timings)
1st September @ 10:30 AM – 11:30 AM (EST) (U.S Timings)
1st September @ 3:30 PM – 4:30 PM (BST) (UK Timings)
Class Schedule:
For Participants in India: Monday to Friday @ 8 PM – 9:30 PM (IST)
For Participants in the US: Monday to Friday @ 10:30 AM – 12:00 PM (EST)
For Participants in the UK: Monday to Friday @ 3:30 PM – 5:00 PM (BST)
What student’s have to say about Trainer :
|
👩 Excellent trainer with real-time examples and hands-on Azure Data Engineering sessions. – Sneha 👨 The trainer explained Azure Data Engineering concepts with excellent real-time examples. The hands-on labs and end-to-end project made learning practical and engaging. Highly recommended for anyone looking to build a career in Data Engineering. – David 👩 Excellent course with well-structured content and interactive sessions. I gained practical experience in Azure Data Factory, Databricks, and PySpark. – Sarah 👨 This course is well-structured and packed with practical knowledge. The trainer made complex Azure Data Engineering concepts easy to understand with live demonstrations. I especially enjoyed learning Azure Data Factory, Delta Lake, and Synapse Analytics. The AI-powered development sessions using GitHub Copilot were an added advantage. It was a fantastic learning experience from start to finish. – Arjun 👩 The trainer’s industry expertise and real-time demonstrations made complex topics easy to understand. I now feel confident working on Azure Data Engineering projects. – Emily |
What will I learn by the end of this course?
- Understand Modern Azure Data Engineering Architecture.
- Build Azure Data Factory (ADF) Pipelines for batch data ingestion.
- Store and manage data using Azure Data Lake Storage Gen2 (ADLS Gen2).
- Develop scalable PySpark Transformations in Azure Databricks.
- Implement Medallion Architecture using Delta Lake.
- Query and analyze data with Azure Synapse Analytics.
- Leverage AI Tools for faster Development, Debugging, Code Generation, and Documentation.
- Build and showcase a Real-World End-to-End Azure Data Engineering Project.
Salient Features:
- 30 Hours of Live Training along with recorded videos
- 1 Year access to the recorded videos
- Course Completion Certificate
Who can enroll for this course?
- Aspiring Data Engineers looking to build a career in Azure Data Engineering.
- ETL Developers who want to upgrade their skills with Microsoft Azure and modern data platforms.
- SQL Developers interested in cloud-based data engineering and data pipeline development.
- Data Analysts looking to transition into Azure Data Engineering roles.
- Software Developers who want to learn Azure Data Factory, Databricks, and PySpark.
- Cloud Engineers interested in data engineering solutions on Microsoft Azure.
- Business Intelligence (BI) Professionals working with data warehouses, reporting, and analytics.
- Data Warehouse Professionals looking to modernize their skills with Lakehouse architecture and Delta Lake.
- Fresh Graduates seeking a career in Cloud Data Engineering with hands-on project experience.
- IT Professionals who want to upskill in Azure Data Engineering, AI-powered development, and real-world data pipeline implementation.
Course syllabus:
Module 1: Data Engineering Foundations + Azure Basics
- What is Data Engineering?
- Data Engineer Roadmap
- Modern Data Platform
- ETL vs ELT
- Batch vs Streaming
- Data Warehouse
- Data Lake
- Lakehouse
- Medallion Architecture
- Azure Data Engineering Services
Hands-on
- Azure Account Setup
- Resource Group Creation
- Storage Account Creation
Module 2: Azure Storage & Data Lake Gen2
- Blob Storage
- ADLS Gen2
- Containers
- File Structure
- Security
- SAS Tokens
- RBAC
Lab
- Create
- Raw
- Processed
- Curated
- Archive
- Logs
- Upload CSV
- Explore folders
Module 3: Azure Data Factory Fundamentals
- Pipeline
- Dataset
- Linked Service
- Copy Activity
- Parameters
- Variables
- Dynamic Content
Lab: CSV -> Azure Data Lake -> Azure SQL
Module 4: Azure Data Factory Advanced
- Lookup
- ForEach
- Incremental Load
- Metadata Driven Pipelines
- REST API
- Error Handling
- Triggers
Lab: Build Dynamic Pipeline
Module 5: Azure Databricks & PySpark
- Workspace
- Cluster
- Notebook
- Spark Basics
- DataFrame
- Reading Files
PySpark
- select()
- filter()
- groupBy()
- joins()
- window()
- write()
Lab: Clean sales dataset
Module 6: Delta Lake + Medallion Architecture
- Delta Tables
- ACID
- Time Travel
- Merge
- Upsert
- Vacuum
- Optimize
Lab: Bronze -> Silver -> Gold Pipeline
Module 7: Azure Synapse Analytics
- Serverless SQL
- Dedicated SQL
- External Tables
- Spark
- Query Data Lake
Lab: Create reporting layer
Module 8 — AI + Azure Data Engineering
AI-assisted Data Engineering
- Generate and explain SQL with AI
- Generate/debug PySpark
- Generate ADF expressions
- Debug pipeline failures with AI
- AI-assisted data quality checks
- AI-assisted documentation
- GitHub Copilot
AI Data Engineering concepts
- What is RAG?
- Embeddings
- Vector search
- Chunking
- Metadata
- Document ingestion
- Building a simple AI-ready data pipeline
Module 9: End-to-End Project
Capstone Project: CSV -> ADF -> ADLS -> Databricks -> Delta -> Synapse -> Power BI
Deliverables:
Students will receive:
Git Hub notes
PySpark notebooks
Azure Data Factory pipelines
SQL scripts
Architecture diagrams
AI prompt library for Azure Data Engineering
Assignments after each session
One end-to-end capstone project
Session recordings
GitHub repository with all source code
How can I enroll for this course?
OR
For any other details, Call me or Whatsapp me on +91-9133190573
Live Sessions Price:
For LIVE sessions – Offer price after discount is 300 USD 259 119 USD Or USD13000 INR 12900 INR 9900 Rupees