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7 Tips For Data Science Newbies

To help make your learning journey easier.

Photo by Siora Photography on Unsplash
Photo by Siora Photography on Unsplash

During the lifespan of our lives, we go through various learning and self-developing. The start of any journey is always challenging; you don’t know the right way; you’re unsure what to expect or how to overcome the bumps in the road.

Joining a field like Data Science is both intimidating and rewarding. It is intimidating because the field is vast and has many options for what you could do. But as a beginner, you don’t know what you like, so you have to feel everything before you settle on a topic.

Once you choose a topic and start mastering it, the learning process goes from terrifying to enjoyable. Navigating your way in a new field is a tough task if you’re a newbie. You don’t have enough knowledge to make decisions, and you don’t fully comprehend what is out there.

The purpose of this article is to give you 7 tips that can help you navigate your learning journey better and easier. These tips are not about what to learn to become a data scientist; they are also not about resources you can use to grow your knowledge. They are tips on how to approach your learning journey, so it becomes hassle-free.

A Learning Path To Becoming a Data Scientist

These 7 tips are the results of teaching and mentoring kids, teenagers, and adults for over 5 years. Without further ado, let’s get into it…

Tip №1: Start with a slow and steady pace

They say beginnings are the most difficult. I agree with that statement. That’s why I believe that the best way to start learning something new is to start at a slow and steady pace.

The best approach is to make a daily schedule to learn and build something every day. The trick to improving is to stay consistent. I often see when people start a new thing that they are so excited and really into it in the beginning. They try to learn as much as they can as fast as they can.

That strategy is rarely successful. When we aim to learn something fast, we often skip important steps in the learning process and only understand its effects later. So, start small, take steady steps, and practice daily.

Tip №2: Focus on building a strong foundation

Following the 1st tip, if we tackled the journey without appropriate planning, we won’t build a strong foundation. What happens when your foundation is shaky? That’s right; you’re building collapses.

Data Science is not a stand-alone field. In fact, it is an interactive inter-disciplinary field built upon various other fields such as maths, statistics, and scientific learning. To get started with any data science subfield – has it be machine learning, artificial intelligence, or natural language processing – you need to work on building your foundation first.

Start with learning how to program, not just the bare minimum, but how to program efficiently and produce quality code. Work on your maths and statistics basics before jumping into implementing different algorithms.

Building a solid basis will take some time initially, but, trust me, it will save you much, much time in the future.

Tip №3: Build and don’t browse

We all tend to make a widespread mistake – myself included – is our tendency to browse and not build. What I mean by that is, we browse tutorials online, read books, and skim research papers. And that’s it.

Most newbies don’t actually try and apply this knowledge and use it to build something. That’s the tricky part, if you don’t build things by hand, you won’t make mistakes, and mistakes are how we learn.

Start building your portfolio right away, try to use all the new information you learn in a project, and add these projects to your portfolio. Don’t worry if the projects are small and simple; remember, even the highest towers start with a stone.

4 Types of Projects You Must Have in Your Data Science Portfolio

Tip №4: Don’t wait too long to start contributing

One of the most challenging things to master is, knowing when to take your knowledge out. When we start learning new things, we wait till we "know enough" before we start taking our knowledge out by applying to jobs or preparing for interviews.

But, the thing is, "know enough" is not a constant factor. It is a very subjective term. I might think I don’t know enough to build a good project or apply for a role when that’s not true. We often tend to underestimate our own knowledge and seek perfection.

This is impossible, especially in a field like data science. It’s a field that has new and exciting advances every day. You’ll never know everything; no one will ever accomplish that.

So, once you built your foundation, learned the basics of the fields, start building interesting projects, and applying for entry roles while continuing to expand your knowledge.

Tip №5: Practice efficient visualizing and communications

Data science is a field all about stories told through data. You will need effective visualization to see your data’s story and effective communication skills to tell the story.

I consider visualization and communications as pillars for your data science foundation. When you spend a long time collecting data, cleaning, exploring, and modeling it, finding interesting patterns. But, your visualization is dull and ineffective.

The result of that inefficient visualization is your results will be overlooked and unappreciated. Choosing the correct chart type, colors, and style will make a tremendous difference in how others preserve your results. Practice different visualization styles and observe how efficient each style is and when to use them.

Data Visualization 101: 7 Steps for Effective Visualizations

Tip №6: Teach, mentor, and blog

The best way to fully understand something is to try and teach it to someone else. Once you got your basics straight, start getting this knowledge out. Teach while you’re learning.

There are many ways you can teach others what you know and deepen your knowledge at the same time. The easiest and most accessible approach is to write blog posts documenting what you learned in your journey. Use platforms like Medium or GitHub to write articles about new things you learn.

Not into writing? That’s okay; teach a sibling or a friend whose interest in data science is what you have learned so far. Try to explain things to them in a creative way.

Not into that, either? Then just keep an organized set of notes of what you learned and keep adding it to it whenever you learn something new.

When you try to put your thoughts out – whether on paper or in words – you will be forced to process them, which will allow you to discover any knowledge gaps you might have.

Tip №7: Nourish your curiosity with continuous learning

Data science is a field that’s rapidly developing; new algorithms, techniques, and tools are being built and developed regularly. When you get into this field, you must have a curious mind that always strives to learn new things.

One of the most important things to keep in mind while going through your learning journey is to nourish your curious mind through continuous learning. Read new advancements in the sub-field that interest you most, skim, and go through research papers to know the field’s current state.

Doing so will help you gain a bigger and better picture of the field and will help you navigate your way around the different aspects of the field more efficiently.

Takeaways

Getting into a new field can be difficult to navigate for a newcomer. Having been on both sides of the equation, being a newbie and teaching/ mentoring newbies. I have noticed that people tend to overlook some aspects of the learning process through their journey that would make it much smoother.

Data Science Lingo 101: 10 Terms You Need to Know as a Data Scientist

Because data science is a field with so many dimensions, navigating it especially is a tad harder than some other fields. In this article, we walked through 7 tips that could help you successfully navigate your learning journey and efficiently reach your destination.

Aside from the tips in this article, the most important mindset when starting any learning journey is to keep an open mind and a passion for learning and growing. Just keep trying, practice, and never give up. That’s the only sure equation to reach success.


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