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Capstone Projects: Data Engineering

Capstone Project
Specialized
Fully Ready

About the Course

This self-paced, hands-on capstone project allows students to apply their data engineering skills to build a complete, end-to-end solution, such as an ELT warehouse, ETL pipeline on Azure, or a Delta Lakehouse.

Learning Outcomes

By the end of this course, participants will be able to:

  • Design scalable solutions: Define project requirements and create robust data engineering architectures using ELT, ETL, or Lakehouse patterns.
  • Build and deploy pipelines: Develop end-to-end data pipelines with Azure Data Factory, Databricks, and Spark for efficient data ingestion, transformation, and storage.
  • Incorporate machine learning: Integrate basic ML components (e.g., NLP models) into pipelines to enable data-driven insights and automation.
  • Present project outcomes: Prepare and deliver professional presentations showcasing technical decisions, challenges, and business impact.

Curriculum

  • Chapter 1: Project Description

    Overview:

    Students get introduced to the capstone project, understand objectives, and explore the datasets they will work with. They follow structured steps to plan and prepare their solutions.

    Topics:

    • General project overview and scope
    • Data overview and source guidelines
      • Step 1: Azure Data Factory pipeline creation
      • Step 2: Databricks mount storage container
      • Step 3: Train machine learning model
      • Step 4: NLP prediction
      • Step 5: Create Synapse analytics environment
  • Chapter 2: Project Solution

    Overview:

    Students access sample code and solution walkthrough videos to understand implementation best practices, while still completing the project independently.

    Topics:

    • Reference code for pipelines and ML integration
    • Solution videos:
      • Business requirements overview
      • Data lake pipeline creation
      • ADF linked services and datasets
      • Pipeline activities and triggers
      • Databricks workspace and storage setup
      • ML model training and analysis
      • Final project walkthrough
  • Chapter 3: Project Outcome

    Overview:

    Students finalize and present their projects, highlighting their implementation choices, challenges faced, and the business value of their solution.

    Topics:

    • Student project presentations
    • Demonstrate technical decisions, project outcomes, and business impact

Tools

Azure Data Factory (ADF), Azure Databricks
Spark
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STUDENT REVIEWS

What our graduates are saying

I had an incredible experience at this data science bootcamp! Coming in with no prior knowledge, I was amazed at how quickly I gained a solid understanding of the field. The curriculum is intensive and hands-on, allowing me to learn real, applicable skills through working on real client projects. The staff are exceptionally supportive and always ready to help. This bootcamp truly transformed my career path, and I couldn’t be more grateful for the knowledge and confidence I’ve gained. Highly recommended for anyone looking to break into data science!

My experience was awesome. I was taught by professional data engineers who shared their insights based on their professional experience. The topics covered are relevant to what employers are looking for and I enjoyed hands-on projects. I learned all the skills I needed to be a data engineer and I got a full-time offer as a data engineer, thanks to the mentors from WecloudData. I highly recommend this program. I was able to land interviews at Amazon, Yelp, CI Financial e.t.c

Deciding to go with WeCloudData was one of the best decisions I made during my career switch. Their Bootcamps are intense but they get you where you need to go. The instructors are amazing and the TAs very knowledgeable. Their client projects taught me a lot even after the bootcamp was done. I was able to land my current job thanks to the skills and training from the course.

I had the pleasure of attending WeCloudData’s Data Fundamentals bootcamp, which was fantastic. The highly qualified instructors used cutting-edge teaching techniques that greatly facilitated understanding the logic of coding and programming. They carefully progressed us from fundamental to more complex subjects, avoiding any feeling of overload. I wholeheartedly endorse this course for anyone hoping to become a data analyst—it’stheonly one you’ll need. The teachers are very outstanding!

This bootcamp provided me with the necessary technical skills and industry knowledge to secure a data job. The instructors are knowledgeable and shared everything they know to help me achieve my goals. The TAs are resourceful and patient answering my questions. The projects in the bootcamp enhanced my knowledge and impressed interviews. This is a wonderful bootcamp if you are looking to either imporve your skills or switch career!

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Common Questions

Find answers to your questions about the Learning Track
  • Standard Courses: Focused, short courses that build foundational or intermediate skills through hands-on exercises, enabling you to apply what you learn immediately.
  • Track Courses: Structured learning paths that guide you from beginner to advanced levels. They include practical projects that integrate multiple tools and workflows, aligned with industry best practices, helping you gain the skills and confidence to tackle real-world challenges.

No. Track Courses are only accessible through the Professional or Unlimited+ subscription plans.

  • Standard Plan gives you access to all Standard Courses.
  • Professional Plan gives you access to both Standard and Track Courses within your chosen domain.
  • Unlimited+ Plan provides full access to all courses — both Standard and Track — across all domains.

 

Yes, all courses are designed to be self-paced. Learn when it fits your schedule.

Each course includes prerequisites if needed. Many Standard Courses are beginner-friendly.

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