Q: What is the DEP Data Engineering Open Track?
The DEP Data Engineering Open Track is a six-month, community-powered, project-driven learning journey. It guides aspiring data engineers through building, deploying, and owning a production-grade data pipeline from scratch.
Q: Is this a bootcamp or a traditional course?
No. It is an anti-course: no traditional lectures, no hand-holding tutorials, and no spoon-fed answers. The program provides milestones, review guardrails, and community support, but you are responsible for researching, debugging, and executing your own project.
Q: Is there a tuition fee? What's the catch?
The program is 100% free and community-powered. The only currency expected is your time, grit, and commitment to meeting weekly project milestones.
Q: Will I get a certificate at the end of the program?
Finishers earn official recognition as a DEP Certified Builder. The real proof is a live end-to-end data pipeline, a well-documented GitHub repository, and a public dashboard hosted on GitHub Pages.
Q: How much Python and SQL do I need before joining?
You should already have a solid foundational baseline: basic Python syntax, data types, loops, and fundamental SQL queries such as joins, aggregations, and filtering. The cohort focuses on using those tools in real data pipelines and deployable projects.
Q: What are the hardware and system requirements?
You need access to a functional laptop or desktop computer and a stable internet connection. Your system must support a local Python environment, a code editor such as VS Code, and Git commands.
Q: What technologies will we be using?
The curriculum uses a lean open-source stack: Python, SQL, Git/GitHub, and APIs to ingest, transform, move, and visualize data.
Q: What is the time commitment required for the cohort?
You should commit at least 5 hours per week for 6 months, or roughly 120 hours total. The rhythm is self-paced through the week, with milestone target deadlines to help you stay on pace.
Q: I have a full-time job or a heavy school load. Can I still join?
Yes. The pacing is meant to work for students and working professionals, but you still need to protect those 5 hours each week. If you cannot commit to the finish line, do not take a slot from someone who can.
Q: What happens if I miss a milestone deadline?
Your issue remains open and continues through the normal automated checks, prerequisite queue, and human review. The system adds a late-submission indicator so the timing stays visible, but it does not reject or close the issue. Do not open a replacement issue; post /recheck <40-character-hash> on the original issue if revisions are requested.
Q: I don't know what project to build. What do I do?
Start with a question you genuinely want answered. Good public-data topics include traffic and transport, crop prices and agriculture, health facility access, flood and typhoon patterns, and education statistics. Your project does not need to be groundbreaking. It needs to be answerable with real data.
Q: Why is the cohort limited to only 50 participants?
We limit the inaugural cohort to 50 builders so the team can provide meaningful code reviews, mentorship, and community accountability.
Q: How does the Selection Committee evaluate applications?
Applications are reviewed for foundations, resources, intent, and grit: Python and SQL familiarity, the hardware and internet needed to participate, clear motivation to learn and execute, and visible commitment to finishing the six-month journey.
Q: If I don't get selected, what are my options?
Not being selected does not end your journey. You can continue building your skills through free resources from our official partners, DataCamp and WorldQuant University. You can also explore learning materials, past sessions, and community activities available through the Data Engineering Pilipinas website. Stay engaged, keep learning, and feel free to apply again in the next cohort cycle.