Main Course of the Academy
This is the new main course of the academy for students who upgraded to unlimited access.
Use this as the main curriculum after your Annual Access has passed.
Curriculum
Introduction
Available in
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after you enroll
1 The Basics
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after you enroll
- 1.1 Introduction to Data Engineering
- 1.2 Computer Science Fundamentals
- 1.3 Introduction to Python
- 1.4 Python for Data Engineers
- 1.5 Data Preparation & Cleaning for Machine Learning
- 1.6 Docker Fundamentals
- 1.7 Successful Job Application
- 1.8 SQL for Data Engineers
- 1.9 Becoming a Better Data Engineer
- 1.10 The Hidden Foundation of GenAI
2 Platform & Pipeline Design Fundamentals
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days
days
after you enroll
3 Fundamental Tools
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days
days
after you enroll
- 3.1 API Design with FastAPI
- 3.2 Apache Airflow Workflow Orchestration
- 3.3 Apache Spark Fundamentals
- 3.4 Data Engineering on Databricks
- 3.5 Apache Kakfa
- 3.6 MongoDB Fundamentals
- 3.7 Log analysis with Elasticsearch
- 3.8 Snowflake for Data Engineers
- 3.9 dbt for Data Engineers
- 3.10 Apache Iceberg Fundamentals
- 3.11 DuckDB for Data Engineers
- 3.12 Spark Declarative Pipelines & Lakeflow Designer on Databricks
4 Hands-On Example Projects
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days
days
after you enroll
- 4.1 Streaming Kafka, Spark, MongoDB, FastAPI and Streamlit
- 4.2 Data Engineering on AWS
- 4.3 Data Engineering on Azure
- 4.4 Data Engineering on GCP
- 4.5 Modern Data Warehouses & Data Lakes
- 4.6 Machine Learning & Containerization on AWS
- 4.7 Storing & Visualizing Time Series Data
- 4.8 Contact tracing with Elasticsearch
- 4.9 Data Engineering on Hadoop
- 4.10 Dockerized ETL with AWS TDengine and Grafana
- 4.11 Azure Data Pipelines with Terraform
- 4.12 Semantic Log Indexing & Search
- 4.13 GenAI RAG with LlamaIndex & Ollama
- 4.14 Building Advanced Pipelines with Kestra on GCP
5 Bootcamps & Tracks
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days
days
after you enroll
Copy of 5 Certifications
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days
days
after you enroll