Updated on 20 Sept 2022

Top 5 Motivational Tips for Studying Data Science

Dessie Tsvetkova Published on 20 Sept 2022 5 min read

With the rising popularity of data science, more and more people are embarking on learning journeys to gain the necessary skills for this in-demand field. With this comes a plethora of resources for prospective students.

From university specialization such as MIT and professional certification from reputable names like IBM to dedicated platforms for online learning like edX, Udemy, and 365 Data Science, aspiring data scientists are spoilt for choice. Yet, the completion rate for MOOC data science courses is less than 15%.

There could be many reasons for this – feelings of discouragement or external responsibilities can easily distract you from learning, especially if you’re doing it in your own time. This raises the question: how do you stay motivated when studying data science?

At 365 Data Science, we know it’s hard to practice self-encouragement when learning online – it feels like it’s only you against the world. But you need to persevere if you’re truly set on this path toward success. In this article, we’ll give you 5 motivational tips to stay on top of your data science studies.

Studying Data Science: Table of Contents

Tip 1: Define Your End Goals

First and foremost, think about what you want to achieve and why. Are you learning data science because you have a new-found passion you want to turn into a career or because of the high salaries? It can be both, of course. No matter the answer, it needs to resonate so you feel like the effort is worth it.

Take one of our success stories for example – Kiran B. used to work in hospitality before the pandemic decimated the travel industry. Feeling stuck, he turned to data science with the goal to have a stable income and do something he enjoyed. After defining his objectives, Kiran felt more motivated to stick with online education, even dedicating 3 to 4 hours a day to it. He now holds over 14 industry-recognized data science certificates and works as a data analyst.

If you’re just dipping your toes into the field of data science, spend some time learning the different roles – you can browse through a selection of useful resources in our Career Guides blog section. When you find one that aligns with your goals or desired lifestyle, you can start building an actionable strategy.

Tip 2: Break Down Your Goals into Manageable Tasks

Data science is an umbrella term for many disciplines. Studying them all, especially if you’re a complete beginner, is a lengthy process – you may find yourself losing motivation because there’s just so much to do.

That’s why we recommend treating your learning journey as a project. Project Manager defines the term as “a set of tasks that must be completed in order to arrive at a particular goal or outcome.” Whether it’s simple or more complex, you can break down your objective into smaller, more achievable goals.

Let’s say, for example, that you’re learning Python – what is your first course of action?

It’s best practice to get to know the environment first, how the syntax works, the types of libraries and what they’re used for. Spend some time reading the Python documentation to familiarize yourself with the language before you jump into your first notebook. This way, your “project” turns into a less intimidating task than it appeared to be.

A common issue with online courses, compared to traditional ones, is that it’s easy to get lost and demotivated when you have to make your own curriculum. In these cases, we recommend our 365 Career Tracks that streamline the process so you can focus on building the skills for your desired career.

Tip 3: Keep a Consistent Study Schedule

It may be tempting, but don’t try to cram everything in all at once – studying data science is not a buffet. By trying to learn as much as you can in one go, you’re exposing yourself to burnout. Besides, cramming leads to lower long-term retention than studying spaced out over multiple sessions in time. Similarly, if you don’t study regularly, you’re also at risk of losing motivation because you’ve simply not built a habit of it.

Of course, for most people, life isn’t that simple. We understand that you may have other responsibilities in life which make studying hard – such as full-time employment, family, health, and countless other factors.

It’s okay if you can’t dedicate hours on end; not many can. As long as you set some time aside – even just 5 to 10 minutes a day – you’re still well on your way to data science success. As James Clear says in his bestselling book Atomic Habits, “success is the product of daily habits – not once-in-a-lifetime transformations.”

And if you need another incentive, 365 Data Science’s user dashboard allows you to set a daily learning goal that best suits your needs and availability.

Tip 4: Create a Comfortable Study Environment

A clear desk leads to a clear mind. It’s very important to have a dedicated space for learning in a calm environment that allows you to focus on retaining knowledge. Data science is already a complicated discipline without the added pressure of external (de)motivators.

So, set up shop in a room with little to no distractions (that includes your bed!). If you don’t have one, just make sure you’re not tempted by your phone and TV, or side-tracked by family members and roommates who come in for a quick chat.

While some people can work in chaos, others don’t fare well and lose motivation because of a cluttered physical and, therefore, mental space. To get into the proper mindset, set healthy boundaries for yourself and your environment. As data scientist and 365 instructor Ken Jee says, your workplace needs to be designed to optimize for quality work.

Ken also has a fully comprehensive video on how he personally stays motivated and productive while learning data science – check it out below:

Tip 5: Reward Yourself

All hard work requires positive self-reinforcement – otherwise, we may feel deflated and abandon our goals prematurely. You don’t want this to happen, do you? So, to keep the motivation going – and, more importantly, keep building good learning habits – you should reward yourself from time to time.

The reward doesn’t have to be too big, nor too small; it has to be just enough for the task you’ve completed. For example, you can catch up on that TV show episode after meeting your daily learning goal. Or purchase that new tech release you’ve been eyeing after successfully completing a career track.

It can even be something as small as indulging in your favorite snack after watching a whole course section. What’s important is that you begin associating each task completion with something positive. This will give you the drive to move forward with the next one. After all, studying data science can be fun too!

And to make it even more fun, we’ve introduced gamified features to our platform, like experience points, in-app coins, streaks, and unique awards that help you stay on track and motivate you to do the work every day. Read more about the new, fun learning experience in our dedicated article.

Studying Data Science: Next Steps

Becoming data science proficient, as all other specializations, requires resilience and a high degree of self-drive. But the road to success is never easy. You need to stay motivated in order to be your own hero and conquer your own obstacles.

Remember, you’re not alone on this journey. The 365 team is here to help you develop your professional skills and data science proficiency. With a redesigned platform aimed to motivate you and training by world-class instructors, you have all the necessary resources at your disposal. Start learning today with 65% off on our annual plan!

Learn data science with industry experts

Try For Free
Dessie Tsvetkova

Copywriter

Dessie is a Copywriter at 365 Data Science. She holds a Bachelor’s degree in Creative Writing and is currently pursuing a Master’s in Publishing. Her interest in data science is a natural continuation of her coding experience. In her articles, Dessie aims to make breaking into data science simpler and more accessible so that more people can achieve their professional goals.

Top