Learn Data Science in 4 Months! No Coding! No Math!

Hi, I’m searching candidates for data science ( check my previous posts) and I’m tired.

The CVs That Haunt Me

Every week, I open a CV that looks like it was co-authored by Elon Musk and a team of GPTs:

• Skills: Python, R, SQL, Tableau, Power BI, Azure ML, Spark, Hadoop, TensorFlow, Keras, PyTorch, Transformers, GANs, AWS, GCP, Blockchain-for-some-reason( ah , it was in the JD)
• Certifications: "Completed 19 bootcamps in 6 weeks", "Certified AI Rockstar", "Built a chatbot that can talk to my dog"

Me: “Okay wow, impressive.”

So I ask:

Me : “Can you explain how a decision tree splits data?”

Candidate: “Umm… like… based on the data?”

Me :“What’s p-value?”

Candidate : “Umm… it’s the thing… when you… like… visualize… the... probability of things happening… or not?”

Me “How does logistic regression work?”

Candidate “Oh I didn’t use that. I used AutoML.”

Me: "AutoML? So you're a data doctor prescribing pills without knowing the ingredients?"

and many candidates like that who claim to be expert in deep learning and cannot even explain Gradient Decent.

Let me be honest

After 4 years in the field, I still break into a cold sweat when someone asks about Bayes’ Theorem, Standard deviation,Null hypothesis, robabilities and distributions

It’s not that I don’t like stats — it just never calls me back.

Why Are We Doing This?

Somewhere along the way, we turned data science into a menu of buzzwords.

Everyone wants to become a "Data Scientist in 4 months" because:

• You don’t need math.
• You don’t need coding.
• You don’t even need to blink — just enroll, click buttons, export CSVs and BOOM: you're a data ninja.

The Harsh Truth

Data Science = Data + Science. Science = Hypothesis + Experiment + Math. Take away the math, and you’re left with PowerPoint.

You can’t solve real-world problems just by dragging and dropping boxes in a UI. Eventually, someone will ask you: “Why?” And if your only answer is “Because AutoML did it”

My Sincere Advice

If you're starting your journey, or struggling in interviews, here’s what I wish more people did:

1. Fall in love with the “why” — Don’t memorize algorithms. Understand why they work.
2. Focus on fundamentals — Learn statistics, probability, and basic linear algebra. These are your best friends. Yes, even that annoying matrix.
3. Code from scratch — Rebuild a regression model without sklearn. Make a decision tree using dictionaries. Cry. Repeat.
4. Be okay with being confused — The people who look smart often spent years being confused quietly.
5. Don’t chase hype — GANs are cool, but can you explain mean and variance?

From the Desk of a Tired Interviewer

LEARN THE FUNDAMENTALS.

Data Science is a long road. Don't look for the elevator. Start climbing the stairs.

#DataScience #CareerAdvice #SatireButTrue #FrustratedInterviewer #MathIsSexy #CVRealness