Data Engineer in Training → I build scalable data pipelines. Computer Engineering student, writing about data, tech and engineering.
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What's one tech skill you think everyone should learn?
→ SQL
→ Python
→ Cloud
→ Git
→ Something else?
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You can know how to code without knowing how to engineer.
You can know how to engineer without knowing how to code.
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TechP retweeted
I met a former NASA engineer this year
And for 6 weeks, I was mentored by him
That short window gave me courage and clarity I didn't know I needed
I got a clear long-term vision
The boldness to apply for jobs
How to be interview-ready
Just six weeks, and it was worth every minute
It shaped the engineer I am today! 🥹
Now, the good news is my birthday is this October
So rather than keep what I learned to myself, I'm hosting a Founder's Day celebration for @yfe_embedded! 🥳🎉
Theme is 'How to Become a World-Class Engineer.' 🔥
And the speaker is Davis Booth, the former NASA engineer who mentored me
We'll cover:
• What it means to be an engineer
• Why to take your career seriously now
• Positioning for local, national, and international opportunities
• Acing interviews
• Job and skill acquisition
So on the 25th October at 4pm WAT (UTC+1), we mount! 🙂↕️
All for a small price of ₦10,000
Students, entry-level, or mid-career professionals, trust me...
You want to be in this room
Register here
👉🏽 bit.ly/4xLnxaE
And I'll see you in class ✨
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TechP retweeted
If you are self learning Data Analysis, you need to read this!! 👇👇
I’m self-taught, and if I had to start my Data Analysis journey again, these are 10 things I would tell myself from day one;
1. Choose your direction
You don't have to specialize immediately, but having an idea of the industry or type of Data Analyst you want to become helps you know what to prioritize.
2. Get a roadmap
Don't learn randomly. Know what you need to learn, in what order, and why you need it.
3. Don't learn every tool
You don't need SQL, Python, Power BI, Tableau, R, Excel, and every new tool you see online. Learn what your target role actually requires.
4. Find your people
Join a community or intentionally build relationships with other people learning or working in data. The journey becomes easier when you don't feel like you're doing it alone.
5. Learn by doing
Don't wait until you "finish learning" before practicing. Learn something today and find a way to apply it today.
6. Solve real questions
Instead of only following tutorials, ask questions that a business could actually care about and use data to answer them.
7. Build projects with a story
A project shouldn't just be "I cleaned this dataset and created a dashboard."
Explain the problem, your analysis, what you discovered, and what someone should do with the insight.
8. Build in public
Share your projects, lessons, mistakes, progress, and wins. You are not just documenting your journey, you're giving people a reason to discover your work.
9. Filter the noise
There will always be another tool, certification, course, trend, or "you MUST learn this" post. You need to know what is relevant to your path and ignore the rest.
10. Give yourself time
You will feel behind. You will compare yourself with people who started before you. You will sometimes feel like you know nothing. Keep going anyway. Consistency compounds.
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Algorithm, connect me with robotics and embedded systems engineers from all over the world. 🌍
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