Courses

The Data Engineer program prepares you for one of the most in-demand roles in modern data infrastructure. Developed by Microsoft, this comprehensive program teaches you how to design, implement, and manage data solutions in the cloud using Azure Synapse Analytics, Apache Spark, and Azure Stream Analytics. You’ll gain hands-on experience building serverless SQL queries, performing large-scale data transformations, integrating hybrid transactional and analytical processing (HTAP), and implementing real-time streaming solutions. Whether you're transitioning into data engineering or looking to deepen your expertise in Azure's data ecosystem, this program provides the technical foundation and practical skills to support enterprise-grade data solutions.

This learning journey provides the required knowledge on using the data provisioning tools for SAP HANA and the use of the data modelling capabilities that are available in SAP HANA to prepare yourself for the assessment to stay certified.

Master Data Engineering, Build Scalable Pipelines, and Land a High-Paying Job. Learn with a Silicon Valley Data Engineer What you'll learn: Understand the Fundamentals of Data EngineeringMaster Advanced SQL for Data EngineeringBuild and Manage Data PipelinesWork with Cloud Data Engineering ToolsOptimize Data Storage and WarehousingImplement Best Practices for Security and Cost ManagementTroubleshoot and Monitor Data PipelinesPrepare for Data Engineering Interviews Data Engineering Bootcamp: From Beginner to Job-Ready!Want to break into Data Engineering? Or level up your skills to land a high-paying job? This bootcamp will take you from beginner to job-ready, helping you master the tools, technologies, and best practices used by top tech companies like Meta, Google, and Amazon.Taught by industry expert Shashank Kalanithi, a software engineer at Meta, this bootcamp is packed with real-world projects, hands-on exercises, and career insights to fast-track your success in data engineering.What You’ll Learn & Achieve:Get a clear roadmap into Data Engineering – Understand what data engineers do, career opportunities, and how to get hiredMaster Advanced SQL for Data Engineering – Work with complex queries, optimize databases, and impress hiring managersBuild & Automate Data Pipelines – Learn Apache Airflow, ETL/ELT processes, and orchestration toolsCloud Data Engineering – Work hands-on with AWS, Azure, and Google Cloud tools like AWS Glue, Azure Data Factory, and GCP BigQueryOptimize Performance & Security – Learn how to manage costs, secure data, and implement logging and monitoring. Troubleshoot Like a Pro – Handle pipeline failures, outages, and performance bottlenecks with confidenceCrush Data Engineering Interviews – Gain insider tips, real-world case studies, and must-know technical conceptsBuild a Job-Winning Portfolio – Apply what you learn through hands-on projects that showcase your expertiseWhy This Bootcamp?Learn in-demand skills used by top tech companiesHands-on projects to build real-world experienceTaught by an industry expert with Meta & tech experienceJob-ready content to help you land a data engineering roleLifetime access – Learn at your own pace, anytime! This is your fastest path to a career in Data Engineering. Don’t waste months figuring it out on your own—get structured, expert-led training and land high-paying opportunities in tech!Enroll now and start building your future in Data Engineering today!

Prepare for one of the most sought-after roles in tech with the Associate Data Engineer in Snowflake track. You'll build a strong foundation in SQL, data modeling, and database design while developing hands-on experience using Snowflake, one of the fastest-growing AI-powered cloud data platforms in the world. Get up to speed with Snowflake’s architecture, features, and performance benefits through interactive courses and tutorials. You'll practice core skills like ingesting, manipulating, and querying data in Snowflake using Snowflake SQL. This track gives you the skills to manage real-world data workflows, from joining and transforming data to modeling schemas. You'll see how to build scalable pipelines, and you'll apply what you learn in a practical project that simulates building insights for a sports media agency.

Take your skills to the next level with our Professional Data Engineer track. This advanced track is designed to build on the Associate Data Engineer in SQL and Data Engineer in Python tracks. It equips you with the cutting-edge knowledge and tools demanded by modern data engineering roles. Throughout this journey, you'll master modern data architectures, enhance your Python skills with a deep dive into object-oriented programming, explore NoSQL databases, and harness the power of dbt for seamless data transformation. Unlock the secrets of DevOps with essential practices, advanced testing techniques, and tools like Docker to streamline your development and deployment processes. Immerse yourself in big data technologies with PySpark and achieve mastery in data processing and automation using shell scripting. Engage in hands-on projects and tackle real-world datasets to apply your knowledge, debug complex workflows, and optimize data processes. By completing this track, you'll not only gain the advanced skills needed to conquer complex data engineering challenges but also the confidence to apply them in the dynamic world of data engineering.

Prepare yourself for the Microsoft Certified: Fabric Data Engineer Associate exam What you'll learn: Students will learn how to build warehouse and lakehouses on Microsoft Fabric.Students will learn all aspects required to take on the DP-700 exam.Students will learn aspects around ingesting and transforming data into Microsoft Fabric.Students will gain a better understanding on how to use Microsoft Fabric when it comes the data engineering needs. This intensive, comprehensive course is designed to prepare data professionals for the Microsoft DP-700 certification exam, focusing on data warehouse implementation and optimization using Microsoft Fabric. Participants will gain the knowledge and practical skills necessary to design, implement, and manage semantic models, data warehouses , lakehouses that leverage the full power of Microsoft's modern data analytics platform.What are we going to learn First we'll setup the required accounts and tools required to practice along. We will learn how to use Free trial licenses when it comes to Microsoft Fabric.Then we will do a deep-dive into hosting data warehouses in Microsoft Fabric. There are different ways in which we can ingest data into a data warehouse. We will learn how to use Data pipelines, T-SQL and Data Flow Gen2 to ingest data into a data warehouse. We won't be done there. We will learn how to design Fact and Dimension tables within a data warehouse.Next it will be time to perform a deep-dive into Lakehouses. We'll again use Data pipelines and Data Flow Gen2 to ingest data into a lakehouse. We'll learn on how to use Notebooks to in interact with data within a lakehouse.Next comes the Eventhouse. How do we get data into the eventhouse.How do we stream a continuous data streams into the eventhouse. And then how to use the Kusto Query Language to query for data.As per the exam , we need to focus on key security concepts, such as how to secure access to items in Microsoft Fabric.How do we enforce column and row level security. There's a lot to cover when it comes to security in Microsoft Fabric.

Preparation course for Databricks Data Engineer Professional certification exam with hands-on training What you'll learn: Learn how to model data management solutions on Databricks LakehouseBuild data processing pipelines using the Spark and Delta Lake APIsUnderstand how to use and the benefits of using the Databricks platform and its toolsBuild production pipelines using best practices around security and governanceLearn how to monitor and log production jobsFollow best practices for deploying code on Databricks If you are interested in becoming a Certified Data Engineer Professional from Databricks, you have come to the right place! This study guide will help you with preparing for this certification exam. By the end of this course, you should be able to:Model data management solutions, including:Lakehouse (bronze/silver/gold architecture, tables, views, and the physical layout)General data modeling concepts (constraints, lookup tables, slowly changing dimensions)Build data processing pipelines using the Spark and Delta Lake APIs, including:Building batch-processed ETL pipelinesBuilding incrementally processed ETL pipelinesDeduplicating dataUsing Change Data Capture (CDC) to propagate changesOptimizing workloadsUnderstand how to use and the benefits of using the Databricks platform and its tools, including:Databricks CLI (deploying notebook-based workflows)Databricks REST API (configure and trigger production pipelines)Build production pipelines using best practices around security and governance, including:Managing clusters and jobs permissions with ACLsCreating row- and column-oriented dynamic views to control user/group accessSecurely delete data as requested according to GDPR & CCPAConfigure alerting and storage to monitor and log production jobs, including:Recording logged metricsDebugging errorsFollow best practices for managing, testing and deploying code, including:Relative importsScheduling JobsOrchestration Jobs With the knowledge you gain during this course, you will be ready to take the certification exam.I am looking forward to meeting you!

Hello Cloud Gurus!Data management, data analytics, machine learning and artificial intelligence are all hot topics. And who does these better than Google? Our Google Certified Professional Data Engineer course will help prepare you for the certification exam so you can take that next step in your Cloud career and demonstrate your proficiency in one of the most in-demand disciplines in the industry today.The primary focus of this course is to prepare you for the GCP Professional Data Engineer certification exam. Along the way you’ll solidify your foundations in data engineering and machine learning, ensuring that by the end of the course you will be able to design and build data processing solutions, operationalize machine learning models and gain a working knowledge of relevant GCP data processing tools and technologies.This course will teach you how to: Design, build and operationalize data solutions Process data streams in real-time Efficiently store and access data in the cloud Use the GCP pre-trained AI APIs (vision, speech and text) Train and operationalize ML models.The Google Cloud Professional Data Engineer is for data scientists, solution architects, devops engineers and anyone wanting to move into machine learning and data engineering in the context of Google. Students will need to have some familiarity with the basics of GCP, such as: storage, compute and security; some basic coding skills (like Python); and a good understanding of databases. You do not need to have a background in data engineering or machine learning, but some experience with GCP is essential. This is an advanced certification and we strongly recommend that students take the Google Certified Associate Cloud Engineer exam before embarking on this course. However, anyone who is motivated and wants to understand how big data and machine learning is done on GCP will still find value with this course.Keep being awesome, Cloud Gurus!

UPDATED: V25 JULY 2025 | Complete preparation for Databricks Data Engineer Associate certification + hands-on training What you'll learn: Understand how to use Databricks Lakehouse Platform and its toolsBuild ETL pipelines using Apache Spark SQL and PythonProcess data incrementally in batch and streaming modeOrchestrate production pipelinesUnderstand and follow best security practices in Databricks If you are interested in becoming a Certified Data Engineer Associate from Databricks, you have come to the right place! This study guide will help you with preparing for this certification exam. By the end of this course, you should be able to:Understand how to use and the benefits of using the Databricks Lakehouse Platform and its tools, including:Data Lakehouse (architecture, descriptions, benefits)Data Science and Engineering workspace (clusters, notebooks, data storage)Delta Lake (general concepts, table management and manipulation, optimizations)Build ETL pipelines using Apache Spark SQL and Python, including:Relational entities (databases, tables, views)ELT (creating tables, writing data to tables, cleaning data, combining and reshaping tables, SQL UDFs)Python (facilitating Spark SQL with string manipulation and control flow, passing data between PySpark and Spark SQL)Incrementally process data, including:Structured Streaming (general concepts, triggers, watermarks)Auto Loader (streaming reads)Multi-hop Architecture (bronze-silver-gold, streaming applications)Delta Live Tables (benefits and features)Build production pipelines for data engineering applications and Databricks SQL queries and dashboards, including:Jobs (scheduling, task orchestration, UI)Dashboards (endpoints, scheduling, alerting, refreshing)Understand and follow best security practices, including:Unity Catalog (benefits and features)Entity Permissions (data objects Privileges) With the knowledge you gain during this course, you will be ready to take the certification exam.I am looking forward to meeting you!

Databricks Data Engineer Associate Course with Practical Examples & Hands-On Training, Master Databricks Skills What you'll learn: Databricks Clusters, Notebooks, data storageDatabricks Lakehouse Platform (architecture, descriptions, benefits)Delta LakeELT with Spark SQL and PythonRelational entities (databases, tables, views)Accessing Data from Azure Data Lake Storage (ADLS)Structured Streaming, Auto LoaderDelta Live Tables, Multi-hop ArchitectureDatabricks JobsDatabricks DashboardsData Governance Welcome to our comprehensive course on Databricks Certified Data Engineer Associate certification. This course is designed to help you master the skills required to become a certified Databricks data engineer associate.Databricks is a cloud-based data analytics platform that offers a unified approach to data processing, machine learning, and analytics. With the growing demand for data engineers, Databricks has become one of the most sought-after skills in the industry.In this course, you'll learn the core concepts of Databricks, including Databricks Lakehouse Platform, ELT with Spark SQL and Python, Incremental Data Processing, Production Pipelines, and Data Governance.This course is designed by industry experts with years of experience in Databricks and data engineering. This course has theoretical concepts and hands-on labs to help you apply the concepts learned in the course.Upon completion of the course, you'll be able to take the Databricks Certified Data Engineer Associate exam with confidence and succeed in your career as a data engineer. At the end of this course you should be able to: Understand how to use and the benefits of using the Databricks Lakehouse Platform and its tools, including:Data Lakehouse (architecture, descriptions, benefits)Data Science and Engineering workspace (clusters, notebooks, data storage)Delta Lake (general concepts, table management, manipulation, optimizations)Build ETL pipelines using Apache Spark SQL and Python, including:Relational entities (databases, tables, views)ELT (creating tables, writing data to tables, cleaning data, combining and reshaping tables, SQL UDFs)Python (facilitating Spark SQL with string manipulation and control flow, passing data between PySpark and Spark SQL)Incrementally process data, including:Structured Streaming (general concepts, triggers, watermarks)Auto Loader (streaming reads)Multi-hop Architecture (bronze-silver-gold, streaming applications)Delta Live Tables (benefits and features)Build production pipelines for data engineering applications and Databricks SQL queries and dashboards, including:Jobs (scheduling, task orchestration, UI)Dashboards (endpoints, scheduling, alerting, refreshing)Understand and follow best security practices, including:Unity Catalog (benefits and features)Entity Permissions (team-based permissions, user-based permissions) Enroll now and take the first step towards becoming a certified Databricks data engineer associate.

UPDATED JULY 2025 Syllabus | Full Coverage of Databricks Certified Data Engineer Associate Exam | Full Practice Test What you'll learn: All the topics required to PASS the Databricks Certified Data Engineer Associate ExamFull Length Practice Exam with Detailed Explanations IncludedAll 320+ Slides are included as a downloadable PDFDatabricks Lakehouse Platform Architecture & Databricks Workspace ComponentsMedallion Architecture & Implementing a Solution using Medallion ArchitectureGit Integration with Databricks Workspace and Collaboration with Source ControlExtract Transform and Load (ETL) using Apache SparkSpark User Defined Functions (UDF)Incremental Load Processing using Spark Structured StreamingIncremental Data Ingestion via Auto LoaderDelta Lake Architecture, Benefits, Implementation & Performance TuningImplementing Streaming and Batch Workloads using Delta Live TablesData Quality & Exception Handling using Delta Live TablesImplementing Production Pipelines using Databricks JobsConfiguring & Deploying SQL WarehouseCreating Alerts & Dashboards using Databricks SQLConfiguring & Working with Databricks Unity CatalogData Governance & Access Control via Unity CatalogLocal IDE Development using Databricks ConnectShare data securely with Delta SharingQuery external sources using Lakehouse FederationDeploy Databricks resources with Databricks Asset Bundles (DABs) Now fully updated for the July 2025 Databricks Certified Data Engineer Associate exam guide (effective for exams on or after July 25th, 2025). Databricks Data Engineer Associate Certification is a gateway to gain recognition in the industry and open doors to better job opportunities and higher salaries. And it showcases your ability to handle real-world data engineering projects, as well as a way to future-proof your career, and a chance to achieve your professional goals! I want to help you pass the Databricks Data Engineer Associate Certification with ease! I have designed the course to give you the right level of theory and hands-on practice so that you can not only pass the certification exam, but also develop yourself with the right skills required to work in the industry using Databricks. So, I have designed the course with the following in mind It covers all the topics required to pass the certification (including all the new topics from the July 2025 exam guide such as Databricks Connect, Databricks Asset Bundles (DABs), Delta Sharing and Lakehouse Federation)It includes a FullLength Practice Exam with detailed explanations (now updated with questions from the new syllabus from July 2025)It provides detailed explanations of each of topicsIt takes a hands-on approach to learning. 80% course requires you to be working with databricksIt has 2 small projects to give you the practical knowledge required to work in the industryIt's fast paced and to the point. I genuinely value your time. All the 300+ slides are available to download as PDFAll the databricks notebooks created during the course are available to downloadI provide guidance on how to approach the Databricks Exam and pass with ease Beginners are welcome!I teach everything about Databricks from Scratch and provide step-by-step instructions. Disclaimer: This course is an independent preparation resource and is not affiliated with, endorsed by, or sponsored by Databricks, Inc. All instructional content, practice questions, and materials have been originally developed by the instructor based on the publicly available exam guide and real-world data engineering experience. No actual exam content or proprietary Databricks materials have been used or reproduced. About the InstructorMy name is Ramesh and I am going to be your instructor for this course. I am a data engineer with over 25 years of experience working on some of the large data projects, including most recently working for Microsoft UK and some of the top consulting firms. I hold a number of certifications including the Databricks Certified Data Engineer Associate Certification that I am teaching in this course. Over the last 4 years, I've taught over 200,000 students on Udemy, and my courses are highly rated and best sellers. I’m extremely passionate about teaching and committed to making your learning journey enjoyable and worthwhile. I am active in the Q&A section of the course. So, you will be able to ask questions and I will be there to answer your questions! So, if you’re ready to take the next step in your data engineering career and become a Databricks Certified Data Engineer Associate, enroll now, and let’s get started! I look forward to seeing you inside the course!

Learn Google Cloud Professional Data Engineer Certification with 80+ Hands-on demo on storage, Database, ML GCP Services What you'll learn: Grasp Basic Data Engineering & Database ConceptProvision Basic GCP infrastructure services - VM, Container, GKE, GAE, Cloud RunLearn Various Storage Product like Cloud Storage, Disk, Filestore for Unstructured DataStructure Data Solution - SQL, Spanner, BigQueryStore massive semi structure data in BigTable, DatastoreDeploy Data Pipeline on different Data Processing Product - DataFlow (Apache Beam), DataProc (Hadoop/Spark), Data Fusion, Composer(Airflow)Cleanse, Wrangle & Prepare Your Data with DataPrepMachine Learning Basics & its GCP Solution ProductSearch Data Asset from Data catalogVisualize Data by creating Reports & Dashboard with Google Data StudioUse Prebuilt ML API (Vision, Language, Speech) in your applicationApply Auto ML on your own data to build modelBuild Machine Learning Custom Model with Notebook , Scikit Learn LibraryDeploy Scikit-learn Model, Tensorflow as endpoint for predictionDetect Sensitive PII data with Data Loss Prevention (DLP) APIStore process and analyse your petabyte-scale data with Google data warehousing solution cloud bigqueryDecouple application with asynchronous communication Google cloud pub subStore data inside the memory for faster access with memory Store redis database Google Cloud Platform GCP is Fastest growing Public cloud. PDE (Professional Cloud Data Engineer) certification is the one which help to deploy Data Pipeline inside GCP cloud.This course has 16+ Hours of insanely great video content with 80+ hands-on Lab (Most Practical Course)------------------------------------------------------------------Some Feedback about course from STUDENTS : 5 ⭐- Recommended ankits all GCP certification course. all are very much comprehensive & fully practical course.5 ⭐- great overview of all topics, highly recommended course good explaination of the various data services5 ⭐- One of the awesome GCP data engineer course i have ever watched, learned a lot, Thank you @ankit Mistry.5 ⭐- The instructor gives very detailed and easy-to-understand explanations. In addition, he explores the theoretical concepts inside the Google Cloud Console. So, it's very practical, as well. I highly recommened.5 ⭐- Good course with lots of practical work to follow along and learn from.------------------------------------------------------------------Do you want to Deploy Data Pipeline inside GCP.Do you want to learn about different Storage, database, Processing, ML product offering by GCP to get insight about data.Do you want to do Data Processing where Internet's biggest App like Google Search, YouTube, GMAIL (Billion users app) store their data, process data & find meaningful insight with ML from your dataIf Yes, You are at right place.------------------------------------------------------------------Why Cloud, GCP, Certification, Data Engineering ? Cloud is the future , & GCP is Fastest growing Public cloud.87% of Google Cloud certified individuals are more confident about their cloud skills.More than 1 in 4 of Google Cloud certified individuals took on more responsibility or leadership roles at work.------------------------------------------------------------------Google Cloud : Professional Cloud Data Engineer Certification is the best to invest time and energy to scale your data storage & processing demand.I am all exited to help you on your journey towards Google Cloud Professional Cloud Data Engineer Certification.So, I created most practical comprehensive course will prepare you for Professional Cloud Data Engineer certification, having 16+ hours of HD quality video content.------------------------------------------------------------------Why Enroll in this course?I believe in learning by doing and it's very much practical course80+ Hands-on Demo80% Practical's + 20% Theory - Highly Practical courseHighly relevant to exam topicsCovers all major topics related to Storage, Database, processing & MLMinimum on Slides + Maximum on GCP cloud console------------------------------------------------------------------Have a look at course curriculum, to see depth of Course coverage.Major Theme of this certification course are:------------------------------------------------------------------1. Data Engineering & GCP Basic ServicesIn this module I will Start with Data engineering pipeline, Different Types of data : structure data, semi-structured data, unstructured data, some concept related to batch data processing and stream data GCP related concepts like GCP region and Zones, how to create a GCP account & various GCP service being offered from the data engineering perspective. Then we'll see about GCP basic infrastructure services like IAM, VM, kubernetes provisioning, app engine, cloud run and cloud function deployment.------------------------------------------------------------------2. Data Storage in GCPIn this module I will teach you different Data storage product for storing unstructured data, Google cloud storage, file Store, persistent disk storage, local SSD storage and how to do data migration from on-premise to GCP. ------------------------------------------------------------------3. Database Offering by GCPIn this module I will teach you Database solution for storing structured data & semi-structured data. For storing structured data inside GCP we have a Google cloud SQL and a cloud spanner is available. For semi-structured data inside the GCP we have a Google cloud BigTable, DataStore/firestore and for in memory power MemoryStore available------------------------------------------------------------------4. Data Processing in GCPIn This Data processing section we will begin with Data warehousing analytical data processing solution google cloud BigQuery and for asynchronous communication we will see Google cloud PubSub services.For developing complete pipeline inside GCP - Dataflow Apache beam solution inside Google cloud Google cloud DataProc for lift and shift Hadoop and Spark job Without writing code with just drag and drop build complete pipeline with cloud Data fusion Monitor Author and schedule a complete workflow we have a Apache airflow - Cloud Composer is available For sensitive and personally identifiable data detection Data loss prevention API - DLP Search for or all data set at one single place Data Catalog is available------------------------------------------------------------------5. ML/AI offering in GCPIn this module we will begin with basics of Machine learningPrepare your data with intelligent data preparation tool Dataprep before throwing all your data to a machine learning algorithmWe will see different pre-built machine learning API for vision, language and speechDouble auto machine learning model with AutoMLBuilding custom machine learning model with various framework life tensorflow, scikit learn and PytorchBigquery ML for machine learning training with SQLAt the end we will see how to create beautiful reports and visualization with in browser Google cloud data studio tool------------------------------------------------------------------This course also comes with:Lifetime access to all course material & updatesQ&A SectionA 30 Day Money Back Guarantee - "No Questions Asked"Udemy Certificate of CompletionSo, What are you waiting for, Enroll NOW and I will see you inside course.RegardsAnkit Mistry

This course helps learners create a study plan for the PDE (Professional Data Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.

The Google Cloud Professional Data Engineer is able to harness the power of Google’s big data capabilities and make data-driven decisions by collecting, transforming, and visualizing data. Through designing, building, maintaining, and troubleshooting data processing systems with a particular emphasis on the security, reliability, fault tolerance, scalability, fidelity, and efficiency of such systems, a Google Cloud data engineer is able to put these systems to work.This course will prepare you for the Google Cloud Professional Data Engineer exam by diving into all of Google Cloud’s data services. With interactive demonstrations and an emphasis on hands-on work, you will learn how to master each of Google’s big data and machine learning services and become a certified data engineer on Google Cloud.Updated to the latest Google exam requirements in July 2019, this course will prepare you to succeed in your quest to become Google Cloud Certified!

Azure Data Engineer & Analyst | Microsoft Fabric | DP-203 | DP-600 | DP-700 | Microsoft Certified: Fabric Data Engineer What you'll learn: Learn Basic Data Engineering & Database ConceptLearn Various Storage Product like Azure Storage, Queue, File, Table StorageBuild structured data solution with various SQL database optionsStore Semi-structured data with CosmosDBDevelop ETL, ELT Solution with Azure Data FactoryAnalyze Data with Data ware housing system - Synapse analyticsAzure Data Factory Control Flow ActivitiesSynapse SQL in Azure Synapse AnalyticsApache Spark in Azure Synapse AnalyticsAzure DatabricksDelta Lake & Data warehouse in Azure DatabricksWork with real-time analytics using Azure Stream Analytics.Gain practical knowledge of Microsoft Fabric for data ingestion, lakehouse, Power BI integration, and real-time intelligence. Are you ready to become a highly skilled Azure Data Engineer and clear top certifications like DP-203 (Azure Data Engineer Associate), DP-600 (Fabric Analytics Engineer Associate), and DP-700 (Azure Data Analyst Associate)? This Azure Data Engineer MasterClass is designed to give you the knowledge, hands-on practice, and confidence you need to excel in both real-world projects and certification exams.Why take this course?The world is generating data at an unprecedented scale, and organizations need professionals who can design, build, and manage modern data solutions on the cloud. Azure has become a leading platform for enterprise data, and roles such as Data Engineer and Analytics Engineer are in high demand. This course will help you step into these roles with job-ready skills.What this course covers:We start with the foundations of Azure Storage—including Blob Storage, SQL Database, and Cosmos DB for NoSQL solutions. You will learn how to store, manage, and query data efficiently.Next, we dive into Azure Data Factory (ADF) where you will build pipelines, automate workflows, and perform both control flow and data flow transformations.Then we move to Azure Synapse Analytics, covering SQL-based querying and Apache Spark for big data processing. You will gain hands-on experience integrating batch and real-time analytics.In Azure Databricks, you will learn how to work with Delta Lake and data warehousing for large-scale data engineering workloads.We then cover Azure Stream Analytics, enabling you to design real-time streaming solutions for IoT, telemetry, and live dashboards.Finally, you will explore Microsoft Fabric, the newest analytics platform from Microsoft. You will practice ingesting data, building lakehouses, integrating with Power BI, and implementing real-time intelligence scenarios.Learning by doingThis course is filled with hands-on exercises, demos, and real-world role plays that simulate data engineering challenges you will face in interviews and on the job. By applying what you learn in practical scenarios, you will build confidence and mastery over Azure’s data ecosystem.What makes this course different?Covers three major certifications in one MasterClass.Combines theory, practical hands-on demos, and role plays.Designed by industry experts and experienced instructors with years of Azure experience.Focuses on job-ready skills, not just exam preparation.By the end of this course, you will be able to confidently design, build, and manage Azure-based data engineering solutions, clear your certifications, and step into a high-demand career as an Azure Data Engineer.

The ONLY course you need to PASS the AWS Certified Data Engineer Exam | Incl. FULL Practice Exam and Explanations What you'll learn: PASS the AWS Certified Data Engineer Exam (DEA-C01)!Full Practice Exam incl. Full Explanations to ACE the examAll Slides as downloadable PDFAll topics covered & 100% up-to-dateHands-on demos with real-world scenariosBuild & Orchestrate Data Pipelines in AWSData Ingestions with Glue & Data Warehousing with RedshiftFull Data Lake Solutions with S3 & Much More The ONLY course you need to prepare and PASS the AWS Certified Data Engineer – Associate exam (DEA-C01) and become AWS Certified Data Engineer – Associate!Make your exam preparation and learning Data Engineering in AWS fun & easy but very effective: By learning with real-life & hands-on projects, quizzes and a full practice exam!This course teaches you every single topic you need to master the exam with ease. Why is this the ONLY course you need to take to pass the AWS Certified Data Engineer exam?Learn everything you need to know to master AWS for Data Engineering and to prepare and pass the DEA-C01 exam.Every single topic is covered in depth100% up-to-date!Full practice exam incl. all explanationsTips for successEverything you need to know about the exam itselfMany quizzes to test your knowledgeLearn all the practical knowledge to master AWS in the real worldThis course guides you step-by-step to prepare in the best possible way for the examDon’t waste your time but focuses on what really matters to master the exam! The instructor:Hi, my name is Nikolai, and I have just passed my DEA-01 Data Engineer exam. I am teaching AWS and Data Engineering in around 200 countries and my mission with the course: Take the stress out of your exam prep, make it fun but very effective to make the most out of your preparation time. I want to make sure you have the best chances of succeeding and moving your career forward with the AWS Data Engineer exam in your professional career. Enroll now and get:Lifetime access including all future updates22+ hours video lecturesAll project files and source files to downloadFull practice exam with explanationsTips for success30-days-money back guarantee (no questions asked!) What you’ll learn:The only course you need to PASS the AWS Certified Data Engineer examFull Practice Exam including explanations!Master AWS and become a data engineering expertBuild and orchestrate data pipelines in Glue and EMROrchestrate workflows in Step Functions and Glue workflowsBuild data lakes in S3Build data warehouses in RedshiftMaster NoSQL databases like DynamoDB & DocumentDBQuery the data using AthenaManage EC2 instancesBuild event-driven architectures with Lambda and EventBridgeGovernance of data lakes with Lake FormationAccess management with IAMMonitoring with CloudWatchAnd much more! Take this chance, this can be your first step into a successfull data engineering career!Looking forward to seeing you inside the course!

## Advance Your Data Engineering Skills with Python Take your data engineering career to the next level with our Python-focused Track. Building upon the foundational SQL knowledge from our Associate Data Engineer Track, this Track dives deeper into the world of data engineering, emphasizing Python's role in automating and optimizing data processes. ## From Cloud Computing to Advanced Python Programming Your journey begins with an understanding of cloud computing concepts and terminology. From there, you'll progress through Python programming from the basics to advanced topics, including: * Data manipulation and cleaning using powerful libraries like pandas * Importing and exporting data from various sources (CSV, Excel, SQL, JSON, APIs) * Writing efficient, reusable code following best practices * Applying software engineering principles for reliable and maintainable projects Engage in hands-on projects to reinforce your learning and gain practical experience tackling real-world data engineering challenges. ## Master Data Pipelines and Workflow Automation Learn to design and implement ETL and ELT pipelines, automate workflows with Apache Airflow, and use Git for version control in collaborative development. Apply software engineering best practices to build scalable, reliable data pipelines, ensuring efficient data processing and quality management. ## Ideal for Aspiring and Experienced Data Engineers Whether you're an aspiring data engineer looking to break into the field or an experienced professional seeking to enhance your Python skills, this Track is designed to meet your needs. With a focus on hands-on learning and real-world applications, you'll gain the confidence and expertise to tackle diverse data engineering projects. ## Unlock New Career Opportunities As companies increasingly rely on data-driven decision making, the demand for skilled data engineers continues to grow. By completing this Track, you'll be well-positioned to: * Pursue data engineering roles across various industries * Collaborate effectively with data scientists and analysts * Contribute to the development of data-intensive applications * Drive business value through efficient data management and analysis Invest in your future and unlock new career opportunities with the Data Engineer in Python Track.

In today's data-driven world, businesses and organizations are increasingly dependent on structured information to make strategic decisions. This demand has heightened the need for data engineers who can build and maintain robust data infrastructure. In this course, Becoming a Data Engineer, you'll gain a comprehensive understanding of the data engineering role, including the crucial skills and tools required to thrive in this field. First, you’ll explore the fundamental role of data engineering in the data ecosystem, understanding how data engineers collaborate with other data professionals and the main differences between data positions. Next, you’ll discover the essential skills that data engineers utilize in their daily work and the tools that assist data engineers in managing and analyzing vast amounts of data. Finally, you’ll learn various career paths in data engineering, including the educational and experiential routes you can take to enter this field, explore building a data domain portfolio, and see the best practices for professional growth in this career. When you’re finished with this course, you’ll have the fundamental knowledge of the data engineering role needed to understand the responsibilities and the lifecycle of data engineering in the industry.

Learn to build and maintain the infrastructure and architecture for data generation, storage, and processing. This Data Engineer Career Path is your step-by-step roadmap to go from beginner (at any age!) to getting hired as a Data Engineer.Become a top Data Engineer that gets hired this yearFocus on building and maintaining the infrastructure and architecture for data generation, storage, and processingLearn about Data Engineering and how tools like Hadoop, Apache Spark, Apache Flink, Airflow, Kafka, and Spark ML are used in the industryDesign data pipelines that facilitate the flow of data from various sources to storage systems and learn to build Data Lakes with AWSHow to ace all of your interviews, get more job offers and a higher salary

The purpose of this course is to help those who are qualified develop confidence to attempt the exam, and to help those not yet qualified to develop their own plan for preparation.