Azure DataBricks - Data Engineering With Real Time Project (Udemy.com)

in this real time project was not explained

Thank you very much for creating this unique and amazing course! I am not an IT expert but a business professional, and I bought this course to prepare myself for a job opportunity in the data field with Medallion architecture. This course goes through all the concepts in a very detailed and well-explained way. The instructor delivers clear explanations without any pretentiousness, making even complex topics easy to understand. It is a perfect mix of technical information and hands-on practice — and whenever something seemed unclear, the practical exercises made everything click. It’s hard to express how helpful this course has been for me. I truly hope to continue learning from you and to find more courses of this same outstanding quality.

Thank you Raghunathan for creating this exceptional Databricks course. Your efforts are truly appreciated. This course significantly enhanced my understanding of Databricks, with the sections on best practices and performance tuning being particularly valuable for gaining deeper knowledge. As a suggestion for an already excellent course, integrating more real-time examples or practical scenarios into the performance tuning modules would be an invaluable addition, truly enhancing the learning experience. Without a doubt, your course on Udemy is among the very best available, covering all critical aspects comprehensively and proving incredibly helpful for anyone looking to master Databricks.

I recently completed this Databricks course and found it incredibly valuable. The instructor did an excellent job breaking down complex concepts like Spark architecture, Delta Lake, and Databricks workflows into digestible, easy-to-follow lessons. The hands-on labs were especially helpful in reinforcing the material and gave me the confidence to apply what I learned in real-world scenarios. I appreciated the clear explanations, practical use cases, and the thoughtful pacing of the content. This course is perfect for anyone looking to get started with Databricks or deepen their understanding of data engineering and machine learning pipelines on the platform. Highly recommended!

Hi Ramanujan, thank you for this End to End project implementation, All the concepts were clearly explained with practical implementation, I have taken multiple Udemy courses on Azure projects and I must say this is the best project implementation course that is available in Udemy rn, The thing that I liked much about the course is that it is up to date(last week i have completed the course and now i see a new chapter added) and your quick response to the Q &A raised, I hope you will add much more to this course going forward, I will be waiting for any Azure Data Engineer related courses from you....

This course is an absolute gem for anyone who is willing to learn Azure data engineering. It starts from the basics, which might feel a bit slow or boring for those who already have some experience in data engineering. However, it’s still a good refresher to revisit the fundamentals. As the instructor recommends, you can quickly go through the initial sections and jump to Section 5 to accelerate your learning pace and get into the action faster. The real strength of this course is in the way it moves from the basics to advanced concepts with real, practical hands-on exercises. It doesn’t just stop at core data engineering tasks — it also covers important areas like setting up security, integrating with Git repositories, and even building CI/CD pipelines for automation. These additions make the learning experience more complete and practical for real-world projects. What I also appreciate is the clear explanation of tools like Delta/Delta Live Tables, and Unity Catalog, which are essential for modern data engineering solutions. The instructor’s approach is very practical, and you get to build confidence by working through actual project scenarios. Overall, this course is well worth both the time and the money. If you are serious about building your skills in Azure data engineering, I highly recommend this course!

This course offers fantastic content for anyone looking to get started with or deepen their knowledge in data engineering. The concepts are clearly explained, and the course structure flows logically from one topic to the next. I especially appreciated the hands-on projects and real-world examples, which helped reinforce the theoretical concepts. Mr. Ragunathan Ramanujam does a great job breaking down complex ideas into manageable, easy-to-understand lessons. Whether you're new to data engineering or brushing up your skills, this course is a valuable resource. Highly recommended for anyone serious about building a career in data engineering!

One of the well structured databricks courses I've come across. The instructor covers all the key topics which are being used in most of the organisations. I wanted to understand more about the Delta live table,Medallian Architecture,Databricks CI/CD concepts and very happy that these are covered in detail. Can see Raghunathan's wealth of knowledge & experience in the way he organised the course, covering the end-2-end flow of data in a real-time data engineering environment. I would say this course will help for those who are trying to start their carrier in Databricks & those who want to explore more on Databricks.

I recently completed the Azure Data Engineering course, and I must say it has been an incredibly enriching learning experience. This course provides a structured, hands-on approach to learning Azure Databricks, Data Lake, PySpark, Spark SQL, Data Modeling, and CI/CD—all essential skills for a modern Data Engineer. 1. Comprehensive & Well-Structured Learning Path One of the biggest strengths of this course is its logical flow. It starts with the fundamentals of Azure and Data Engineering and gradually moves towards real-world project implementations. The structured format makes it easy to follow, even for beginners, while providing in-depth knowledge for those with some experience. 2. Hands-On, Practical Approach This course is highly practical and ensures that learners apply their knowledge through real-world projects. The hands-on approach with Azure Databricks, PySpark, and Delta Live Tables provides valuable industry-relevant experience. By working on incremental data loads, streaming, and data modeling, learners get job-ready exposure to the latest cloud data engineering practices. 3. Strong Coverage of Essential Concepts The course covers all the critical aspects of Data Engineering, including: ✅ Azure Databricks & Data Lake Integration – Setting up scalable and efficient data storage. ✅ PySpark & Spark SQL – Working with large-scale data processing and optimizing queries. ✅ Data Ingestion & Transformation – Loading data from APIs, databases, and structured files. ✅ Medallion Architecture – Implementing Bronze, Silver, and Gold layers for structured data processing. ✅ Dimensional Data Modeling – Creating fact and dimension tables for data warehouses. ✅ CI/CD & DevOps for Data Pipelines – Automating end-to-end workflows with GitHub ✅ Real-World Project Implementation – A hands-on project to apply learned skills in a professional scenario. 4. Industry-Relevant Curriculum This course is highly aligned with industry standards, making it ideal for aspiring Data Engineers. The inclusion of real-world projects ensures that learners are not just learning theory but actually implementing scalable data pipelines just as they would in a real job. 5. Engaging & Easy-to-Follow Explanations The instructor does an excellent job of breaking down complex topics into easy-to-understand explanations. Whether it’s PySpark transformations, data ingestion techniques, or implementing CI/CD pipelines, the concepts are explained clearly with step-by-step demonstrations.

I am a Data Engineer working in the cloud (Azure) for a private company in the UK. I recently completed this course, which provided me with in-depth knowledge of Databricks in an end-to-end Azure project. Ragunathan taught the course in a very clear and structured manner, explaining not only why Databricks is essential but also how to effectively utilise its components in real-world projects. One of the standout aspects of this course was the exceptional insights into incremental data loading from a source (HTTP Web) to storage. Additionally, the course covered key concepts such as Change Data Capture (CDC) incrementally data processing instead full load in Delta Lake, Spark job tuning, query optimisation, and pipeline design improvements using the medallion architecture to develop a Lakehouse solution. Beyond these advanced topics, the course also covered fundamental Databricks functionalities, including DBUtils, its various use cases, data governance, and the integration of Pandas and PySpark libraries. In my role, I focus on identifying bottlenecks and optimising systems for faster performance. This course has provided me with a solid foundation and significantly enhanced my skills in Databricks and Azure.