Learning curriculum and portfolio projects updated for 2023 — It’s been 5 years since I embarked on my data science journey. I remember how uncertain I felt when I started. After deciding to pursue a career in data science, everyone I spoke to told me to go for a Masters from a top US university. In 2017, that seemed…

And why is everyone talking about it? — Is it just me, or do you also feel like the words “Data-Centric AI” is everywhere? Andrew Ng mentions this in most of his newsletters. Gartner recognizes Data-Centric AI as one of the emerging trends in data analytics and AI in 2022. Landing AI and DeepLearning AI hosted a “Data-Centric…

Digging beyond the standard data profiling — Pandas Profiling was always my goto-secret tool to understand the data and uncover meaningful insights, in a few minutes, under a few lines of code. Whenever I was given a new dataset, I would generate a profiling report first and inspect the data. Only then would I start my exploratory…

#4 Run away from viral articles. — I was on a client call the other day. “You said you mostly write Linkedin and Medium. So, what is your current audience size?” “Oh — I’m not sure; let me look it up.” That was when I realized I had cross 10K+ followers across platforms. A bit of context…

It doesn’t have to be confusing or hard if you listen to the experts — I’ve been questioning my future in data science for a while now. I know for sure I want to be in the data science and AI space, but should I pursue a Ph.D. for an academic career or stick to what I know the best — an industry-focused data science…

You don’t need to have unanswered questions anymore — “So this package creates huge amounts of fake data from this actual data?” “You can say that — but it’s called synthetic data.” “But what’s the point? It’ll be noise. Why don’t you use the actual data itself?” “We can, but there’s not enough data. Also, there are privacy concerns…

An opinionated collection of libraries you definitely would want to checkout — I’m not going to list Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, TensorFlow, PyTorch, etc. You probably know about these already. There is nothing wrong with these libraries; they’re already the bare minimum essential for data science using python. And the internet is flooded with articles about these tools — this piece…

A realistic view of skills interviewers expect from you and how you can achieve them — “I’m a final year student enthusiastic about data science and want to start my career at XYZ. I have done a few data science certifications; what other skills are important for becoming a data scientist?” This is a common question I repeatedly receive in my LinkedIn inbox. It was primarily…

From someone who hated corporates for so long — When I wanted to break into data science, I joined a startup. I’m obsessed with startups, even now. There’s something about the non-hierarchical culture, the own-it attitude, and the growing satisfaction in startups. Honestly, the last thing I wanted to work is a 9–5 job at corporate. But later on…