Data Engineering in the Cloud: AWS S3, PySpark , Dagster, Python – Practical Skills Bootcamp ( DE-PSBA-L1 )

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1. Overview

Welcome to our intensive Data Engineering Bootcamp, designed to provide you with practical, hands-on experience in real-world data engineering. Led by an industry expert, this one-month bootcamp is a project-based learning journey where you’ll develop essential skills using AWS S3, PySpark, Dagster, and Python, creating a fully functional data pipeline from start to finish.

Here’s the description for the Data Engineering in the Cloud: Practical Skills Bootcamp (DE-PSBA-L1):


Data Engineering in the Cloud: Practical Skills Bootcamp (DE-PSBA-L1)

Welcome to our intensive Data Engineering Bootcamp, designed to provide you with practical, hands-on experience in real-world data engineering. Led by an industry expert, this one-month bootcamp is a project-based learning journey where you’ll develop essential skills using AWS S3, PySpark, Dagster, and Python, creating a fully functional data pipeline from start to finish.

Please Note
Once you enroll in this bootcamp, don’t expect recorded videos of live sessions to be available, as we believe in learning through direct, hands-on experience. Your journey begins with our live, interactive classes, where active participation is key. The recorded videos provided in this course outline the flow and topics covered, but the real value lies in live sessions.

Project Focus: Build a Modern Data Pipeline Using Advance Techniques in Data Engineering

2. What You’ll Learn:

  • VSCode & PySpark Setup
  • Ingest Data from API
  • AWS S3 for Data Storage and Serving Layer
  • Data Transformation & Cleaning
  • Build Medallion Architecture (Bronze, Silver, Gold Layers)
  • ETL Pipelines
  • Orchestration with Dagster
  • Automate Data Pipelines

Why Choose This Bootcamp?
In our interactive, 1-hour live sessions held every alternate day, you’ll work directly with your mentor on every aspect of data engineering—from data ingestion and transformation to orchestration and automation of workflows. This isn’t just a theoretical course; it’s an immersive experience where you’ll build a complete data engineering project guided by an expert, but executed by you.

3. Why This Bootcamp is Different

  • No Prerecorded Videos: All sessions are live and interactive, with expert mentors guiding you through real world scenarios.
  • Hands on Learning: Focused on building a real world data pipeline, where you’ll ingest data, transform it, and store it in AWS S3, just like in a big tech company.
  • End to End Project: From data ingestion to pipeline orchestration, you’ll learn by actually doing every step of a data engineer’s workflow.
  • Mentor Support: Daily live sessions and Realtime problem solving with industry experts to help you tackle challenges as they arise.
  • Collaboration & Networking: Collaborate with fellow aspiring data engineers, present your work, and get valuable feedback in a supportive environment.
  • Practical Skills, Not Just Theory: You’ll complete a real project using cloud platforms, orchestration tools, and data engineering best practices, making you job ready by the end of the course.
  • Progress Presentations & Feedback: Present your progress regularly and receive direct feedback from industry experts, ensuring you’re on the right track while improving your problem-solving and communication skills.

 4. Real World Benefits :

  • Industry-Relevant Skills: Work on a practical project that mirrors real-world data engineering challenges. You’ll hit an API to ingest data, transformations, and build a cloud-based data architecture.
  • AWS & PySpark Expertise: Gain hands-on experience with AWS S3 and PySpark, essential skills for modern data engineers working in cloud-based environments.
  • Automation with Dagster: Master data orchestration and automation with Dagster, a tool used by leading tech companies for pipeline management.
  • Collaboration & Networking: Engage in daily discussions with your peers, collaborate on solving real-world data challenges, and receive feedback from mentors who are industry experts.
  • End-to-End Pipeline Mastery: By the end of the bootcamp, you will have built a complete data engineering pipeline, from data ingestion to transformation and orchestration, giving you the confidence to handle similar tasks in the real world.

 5. Tools & Technologies

 Python: The primary language for data analysis.

 Pandas: For data manipulation and exploratory data analysis.

 Dagster: Pipeline Orchestration

 AWS S3: For cloud based data storage.

 PySpark : For Data Transformation

APIs, ETL processes

Bootcamp Structure:

  • Duration: 1 month
  • Live Sessions: 1-hour live mentoring sessions on weekdays (3 days a week)
  • Prerequisites: Python

By the end of this bootcamp, you’ll have successfully built a complete data pipeline, from ingesting data to deploying it using a Medallion Architecture. You’ll gain practical skills and confidence in tackling real-world data engineering challenges, making this project a standout piece in your portfolio. Show potential employers that you have the hands-on experience necessary for top roles in data engineering!

Is This Bootcamp for You?
This bootcamp is ideal for anyone with basic Python knowledge who’s ready to dive into hands-on learning. Our mentor-led approach ensures you’re not just observing but actively building and applying data engineering skills that prepare you for advanced data roles.

Enrollment and Onboarding
Once enrolled, our team will reach out with onboarding details, including access to Microsoft Teams and your start date. Sessions begin on the 3rd, 13th, and 23rd of each month, offering flexible entry points in small, interactive batches.

Prepare to gain practical data engineering skills that will position you for success in today’s data-driven landscape. Enroll today to start your journey! For any queries, contact us at support@instrovate.com or WhatsApp +91 74289 52788.

Average Review Score:
★★★★★

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Course Content

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Data Engineering in the Cloud: AWS S3 & Beyond (1 Month Intensive)
Section 1: Introduction to Data Engineering in the Cloud
Section 2: Data Ingestion and Preparation
Section 3: Data Transformation and Medallion Architecture
Section 4: Building ETL Pipelines
Section 5: Orchestration with Dagster
Section 6: Portfolio Project and Presentation
Section 7: Real-World Applications and Networking
Course Completion
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