This boot camp will help you get the fundamentals needed to be a great data engineer!

Apache Spark Homework Submission

Apache Spark Data Quality Homework Submission

Apache Spark: Architecture, Optimization, and Best Practices Day 1 Lecture

Apache Spark: Hands-On for Broadcast and Hash Joins Day 1 Lab

Apache Spark: Managing Spark Jobs and Notebooks Day 2 Lecture

Apache Spark: User-Defined Functions and Broadcast Join Day 2 Lab

Unit Testing Spark Jobs: Importance, Challenges, and Leadership Perspectives Lecture

Unit Testing Spark Jobs: Mastering Spark and PySpark Testing Lab

Analytical Patterns Homework Submission

Applying Analytical Patterns: Exploring SQL, Scaling Projects and Aggregation Analysis Day 1 Lecture

Applying Analytical Patterns: Mastering Growth Accounting and Retention Analysis Day 1 Lab

Applying Analytical Patterns: Recursive CTEs and Window Functions Day 2 Lecture

Applying Analytical Patterns: Aggregations and Cardinality Reduction Day 2 Lab

Bootcamp Kickoff

Boot Camp Database Setup

Data Pipeline Maintenance Homework Submission

Data Pipeline Maintenance: Navigating the Complexities of Data Engineering Day 1 Lecture

Data Pipeline Maintenance: Strategies for Maintenance and Dock Building Day 2 Lecture

Data Quality Patterns: MIDAS Process from Airbnb Day 1 Lecture

Data Quality Patterns: Spec-Building Document Day 1 Lab

Data Quality Patterns: WAP Patterns Day 2 Lecture

Data Visualization Submission

Data Visualization and Impact: Mastering Data Engineering Day 1 Lecture

Data Visualization and Impact: Hands-On with the CSV files Day 1 Lab

Data Visualization and Impact: Insights and Best Practices Day 2 Lecture

Data Visualization and Impact: Exploring Data Visualization and Aggregation Techniques Day 2 Lab

Dimensional Data Modeling Homework Submission

Dimensional Data Modeling Complex Data Type and Cumulation Day 1 Lecture

Dimensional Data Modeling Complex Data Type and Cumulation Day 1 Lab

Dimensional Data Modeling: Building Slowly Changing Dimensions Day 2 Lecture

Dimensional Data Modeling: Building Slowly Changing Dimensions Day 2 Lab

Dimensional Data Modeling: Graph Data Modeling Day 3 Lecture

Dimensional Data Modeling: Graph Data Modeling Day 3 Lab

Fact Data Modeling Assignment Submission

Fact Data Modeling: Core Concepts, Deduplication Day 1 Lecture

Fact Data Modeling: Practical Insights into Data Modeling Day 1 Lab

Fact Data Modeling: Core Elements in Data Modeling Day 2 Lecture

Fact Data Modeling: Compact Tables for Efficient Data Representation Day 2 Lab

Fact Data Modeling: Minimizing Shuffle and Reducing Facts Day 3 Lecture

Fact Data Modeling: Practical Guide to Formatting and Aggregating Data Day 3 Lab

KPIs and Experimentation Homework Submission

KPIs and Experimentation: Decoding Business Success: Metrics, Growth Strategies and Collaborative Approaches Day 1 Lecture

KPIs and Experimentation: Setting up and Analysing Experiments Day 1 Lab

KPIs and Experimentation: Leading and Lagging Metrics Day 2 Lecture

Flink Homework Submission

Flink Lab Setup

Streaming Pipelines: Mastering Streaming and Real-time Pipelines Day 1 Lecture

Streaming Pipelines: Setting up Streaming Pipelines Day 1 Lab

Streaming Pipelines: Exploring Data Collection and Processing Day 2 Lecture

Streaming Pipelines: Kafka, Postgres, Spark Integrations and Parallelism Day 2 Lab

This boot camp will take you from zero to data engineering hero in 4 weeks

August 15th Kickoff

Intro to SQL 101

GROUP BY, JOIN, and Common Table Expression Lab

Why you should pick data engineering

The Absolutely Free Beginner Data Engineering Boot Camp starting August 14th

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