Or: The Tragic Love Story Between Electronics Projects and Machine Learning Positions
So, picture this:
You walk into a café (because obviously, every intellectual story starts in a café), and you meet a group of “other branch” students. Mechanical, Electrical, Civil—you know, the species who look at Python and think it’s a reptile that lives under the lab bench.
Now, you’re sipping your cold coffee, minding your own business, when one of them pulls out his laptop and says:
“Bro, I just applied for an ML intern position!”
Your curiosity sparks like a short-circuited Arduino. You peek at his resume. And there it is—a masterpiece of irrelevance:
- Project 1: Speed Controller for DC Motors using PID
- Project 2: Power Factor Correction using Capacitors
- Project 3: IoT-based Smart Home (but actually just an LED blinking with Wi-Fi)
…and under “Skills”?
C (Basics), Soldering, and… MATLAB (because apparently, MATLAB is the magic key to AI Nirvana).
And you just sit there, wondering:
“Did I take the wrong career path? Should I start applying for neurosurgery positions with my ‘Hello World’ Python project?”
*Why Do They Do This?
*
Because in their heads, Machine Learning is just another subject they can tune like a circuit. They believe ML = MATLAB, and AI = Auto Increase salary. They think TensorFlow is something you measure in Newtons.
The Great Resume Crime
It’s not just irrelevant projects—it’s the confidence. The absolute Audacity™. They apply for data science roles with projects that literally scream:
“I can fix your washing machine, but don’t ask me to normalize your dataset.”
And then comes the cherry on the top:
They actually expect interview calls. Some even ask,
“Why companies not selecting me, yaar? I have done great projects.”
Yes, Ravi, your PWM-based Fan Regulator is going to revolutionize AI. Maybe ChatGPT will start running on inductors next week.
But Wait… Should We Help Them?
Here’s the philosophical question:
Is it our job, as CS folks, to rescue them from the dark ages of resume-making? Should we take a break from building cool stuff, learning new models, and training LLMs just to teach someone that ‘Machine Learning ≠ Multimeter Learning’?
Or should we just… let natural selection handle it?
Because at the end of the day, we didn’t choose CS so that we could moonlight as career counselors for lost electrons.
We chose this field to build, to innovate, to research, to make breakthroughs—not to spend nights fixing somebody’s resume from “Soldered an LED” to “Trained a CNN.”
**
Final Thought:**
Maybe, just maybe, we help a few—but remember: the world needs researchers, not resume editors.
Top comments (0)