This learning path combines free courses from curated platforms and Google Cloud Skills Boost to help you build strong data engineering foundations.

Week 1: Data Engineering Fundamentals

🎯 Goal: Learn core concepts, SQL, and programming basics.

Week 2: Cloud Computing & Databases

🎯 Goal: Get comfortable with cloud environments and services.

Google Cloud Skills Boost:

Week 3: Data Ingestion & Transformation

🎯 Goal: Learn how to ingest data, clean it, and prepare it for analysis.

Google Cloud Skills Boost:

Week 4: Data Warehousing, Modeling, and Analytics

🎯 Goal: Learn how to design scalable models and query large datasets.

  • Data Modelling Expert Session - details to be identified

Google Cloud Skills Boost:

Week 5: Orchestration, Visualization, and Capstone

🎯 Goal: Build workflows and share results.

Google Cloud Skills Boost

Capstone Project (Optional)

Ingest → Transform with BigQuery → Visualize with Streamlit → Orchestrate with Cloud Composer/Airflow

  • Create a Dashboard in Streamlit to visualize the data
  • Step 1: Ingest data from a public APIs or datasets from here
  • Step 2: Identify a business case to showcase a trend or pattern based on the chosen dataset
  • Step 3: Transform the data using Pandas/Pyspark
  • Step 4: Store the data in BigQuery database
  • Step 5: Create a dashboard using Streamlit to visualize the data
  • Step 6: Create a repository on GitHub and leverage poetry build tool
  • Additional Step: Orchestrate this project in CLoud Composer or Airflow

Repository and Practicalities

Discord

Join the DataTribe Collective Discord server to connect with fellow learners, ask questions, and share your progress. Join here.

Happy learning! 🚀

Acknowledgments

For more details on content usage, dependencies, and non-commercial information, please refer to the disclaimer page.