I’m working night shifts in a BPO, so managing work and learning together can be a little tough. I’m thinking of starting data science and want to know if it’s possible to learn it with a busy schedule.
Yes, definitely. It may be tiring with night shifts, but you don’t need to study for hours every day.
I’d suggest 45–60 minutes on most days and a longer session on your weekly off. Focus on one skill at a time—start with Excel/SQL, then Python, statistics, and machine learning.
Also, don’t just watch courses. Use your free time to build small projects based on things you already understand from BPO, like customer churn, call volumes, or agent performance.
Consistency matters much more than studying 4–5 hours occasionally.
Yes, it’s definitely possible, but consistency is more important than studying for long hours. Even 1–2 focused hours a day can make a difference if you follow a proper learning plan.
I’d suggest starting with Python, SQL, statistics, and data analysis before moving into machine learning. Try to build small projects alongside your learning so you’re gaining practical experience.
If you need a structured path, the HCL GUVI Data Science Course is worth checking out. I also like that it gives you a clear learning path and practical projects, which can make it easier to balance learning with a full-time BPO job.
It’s definitely possible, but please don’t compromise on sleep just to squeeze in extra study hours! Night shifts can be exhausting, and trying to study when you’re already tired won’t help much.
You could make better use of your days off and keep things lighter on working days. Also, a self-paced course might suit you better than one with fixed class timings. There’s no need to rush through everything!
I understand! Managing night shifts and learning something new can be challenging, but it’s definitely possible with a little consistency. You don’t have to spend hours studying every day. Even 1–2 hours at your own pace can make a difference. Start with Python and SQL, and gradually move on to statistics and machine learning. Try setting small weekly goals so you don’t feel overwhelmed while balancing work and learning.