Zach Wilson'sData Engineering Boot campAn intermediate-level, self-paced infrastructure and analytics boot camp to learn efficient data engineering at any scale!
Not meant for entry-level data engineers
Not meant for entry-level data engineers
About The Course
This is a self-paced, 6-week data engineering bootcamp for anyone wanting to break into the field. There are three tracks for you to pick from: the Analytics Track, the Infrastructure Track, or you can select both with the Combined Track. Anyone who buys the course will get a full year of access to my Data Engineering Academy which will be launching in September!
Each week will have a different focus and will include guest speakers with a breadth of industry experience and knowledge and will cover the following:
Curricula
Weeks 1 & 2
These are the data modeling weeks and they are for everybody
- Fact Data Modeling
- The efficient datelist data structure for growth accounting
- Reduced facts for fast long-term analysis
- Normalization vs denormalization
- Dimensional Data Modeling
- When to model as a slowly changing dimension
- The benefits and drawbacks of complex data types like STRUCT and ARRAY
- How to make idempotent pipelines that backfill correctly
- How to properly model dimensions for a graph database
Week 1 & 2 Guest Speakers
Carly Taylor
Senior Manager of ML Strategy at Activision. She has more than 100k followers on LinkedIn.
Ben Rogojan
Seattle Data Guy, YouTube + Substack + Linkedin content creator with 200k+ followers
Joe Reis
Author of the best-selling book Fundamentals of Data Engineering
Stephanie Nuesi
Data Analytics at Google, Linkedin, and Instagram content creator with 250k+ followers.
Week 3
- Prevent and catch data quality errors in dev/prod for Infrastructure Track
- Data quality checks, data validation, and data documentation for Analytics Track
Week 3 Guest Speakers
Alex Freberg
Alex the Analyst, YouTube + LinkedIn content creator with 700k+ followers
Jepson Taylor
Chief AI Strategist at Dataiku
Week 4
- Streaming pipelines with Flink for Infrastructure Track
- Applying analytical patterns and advanced SQL for Analytics Track
Week 4 Guest Speakers
Sundar Velayutham
Senior Staff Data Engineer at Apple
Aishwarya Srinivasan
Data Scientist at Google, LinkedIn, Instagram, and YouTube content creator with 500k+ followers
Week 5
- Batch pipelines with Spark for Infrastructure Track
- Defining KPIs/counter metrics and experimentation for Analytics Track
Week 5 Guest Speakers
Nick Singh
Author of the best-selling book Ace the Data Science Interview, LinkedIn content creator with 150k+ followers
Parth Parekh
Gen AI Data Engineering Lead at Meta
Week 6
Data Engineering
- Data pipeline maintenance and managing on-call for Infrastructure track
- Data impact communication and visualization for Analytics Track
Week 6 Guest Speakers
Jitender Aswani
VP at StarTree, mentored me from junior data engineer to staff data engineer in four years!
Bill Inmon
prolific author and the father of the data warehouse
Week 7
Bonus week, after a one-week break
- LLM-driven data engineering for everybody
Pre-Requisites
The pre-requisites for the Analytics Track are:
- 1+ years of SQL experience
- 1+ years of coding (in Python, Scala, or Java)
The pre-requisites for the Infrastructure Track are:
- 1+ years of SQL experience
- 1+ years of coding (in Python, Scala, or Java)
- You have some exposure to things like Docker and Infrastructure as Code, or you’re willing to learn quickly in the boot camp!
Pricing
- The Analytics Track: $998.50
- The Infrastructure Track: $998.50
- The Combined Track: $1,498.50
To get started, head over to the sign-up page and fill out the form.
After you buy, you’ll receive an invoice that can be used to get reimbursed by your employer if you have a learning budget!