Data Science Courses: Discover Which Learning Approach Is Best For You
From the looks of it, there seem to be more data science courses than data scientists in the world. While this is pretty much what happens in every industry in the prime of its growth (it is also a great sign of the potential of that industry), it does leave learners in a fix. Everything from choosing the right course to deciding on the right university or school becomes a challenge for both fresh learners, just out of school, and professionals looking to upskill. Learning data science too presents a similar situation. Too many courses, online and offline, full-time and part-time, short-term and long-term are available today. Moreover, many professionals talk about the merits of project-based learning (learning by doing) as a better alternative to online data science courses. If you, too, have been wondering if you should enroll in an eLearning data science course or if you should follow a project-based learning approach, this article is for you. We will talk about each in detail and find out which one is right for you.
We will begin by discussing the attributes, merits, and demerits of each learning approach. Next, we will talk about which type of learning is conducive to which type of learner. The fact remains, that no one style is better than the other. It’s only a matter of finding what best suits your learning style, expected outcomes, and time constraints.
Online Data Science Courses
Everyone, from small private institutes to the likes of Stanford and MIT, has online courses that teach data science, Artificial Intelligence, and machine learning. Depending mostly on your financial capacity, you can choose one of these for yourself. Some of the winning advantages of eLearning courses in data science are:
- They are taught by trained professionals who provide all the necessary support, mentorship, and motivation.
- All your questions are answered by said professional, providing plenty of on-demand knowledge. This helps to clear up any doubts as they arise and find real solutions that work.
- The course is structured, providing for well-organized and systematic learning. You begin with the basics and proceed to advanced learning; providing a cohesive and holistic learning experience.
- There are plenty of other learning resources like blogs and tutorials too that add to the experience.
- They are flexible in terms of time and location; allowing you to study from your home, workplace or anywhere you like, at any time you like.
- They offer various price options with quite a few good free courses too. This enables absolutely anyone to pursue the field without having to worry about financial constraints.
So, that sounds like quite a deal, right? If you choose the right one, these online courses can be one of the best ways to approach learning data science. They do present a few challenges though.
- Staying motivated, consistently, is one of the biggest challenges online learners often face. Learning in solitude can lead to boredom and loss of interest, which can affect your momentum and learning.
- Maintaining discipline and staving off distractions is another challenge. When not in a competitive, watchful setting, students could end up losing time on social media or on other unproductive activities.
Project-Based Learning
A better alternative to address the above two disadvantages as well as add some unique benefits is a project-based learning approach. So, you pick a beginner level data science project that involves the skills you are trying to learn and then start working on it. The project, itself, acts as a motivational tool to keep you going and the exposure gained along the way is your education.
As you proceed to build each stage of the project, you will learn all the skills you need. This method is usually more exciting and productive, especially if you choose a project that you love so much that you don’t mind putting in the extra effort.
Some of the advantages of a project-based learning approach are:
- It is more applied and hands-on, allowing for more practical learning, rather than just concepts.
- It is more exciting and provides more motivation to stay on course.
- It helps you quickly build a portfolio even as you learn, making a strong point when applying for data science jobs.
Project-based learning definitely wins in the department of motivation and discipline, which are often more important than information and education. So that could be your ticket to a career in data science. Before you dive in though, this type of learning, too, has its own set of challenges.
Some of which are:
- Project-based learning isn’t as structured as traditional courses, it is more of a "learn as you go." It is you who is the learner as well as the course designer. You could end up learning some more advanced concepts before easier ones.
- It isn’t entirely comprehensive. You’ll only learn the skills required by that project; therefore, you could miss out on some others. The key is to take up various projects and keep learning. Over time, you will have worked on all the important areas and concepts, having honed all the skills it takes to be a good data scientist.
So Which One Should You Pick?
As described here, both project-based and online learning approaches each offers you the ability to learn data science flexibly and build a rewarding career in data science. Which one works better for you depends largely on your personal goals and priorities.
Ideally suited for students and freshers, online courses are right for you if you want a properly structured program that systematically teaches you everything you’ll need to know. If you don’t already have visions of projects you want to do and ideas of your own yet, you’d do well by following a structured program.
If you are already a professional in coding, development or Big Data and are looking to upskill and advance, and you already have some ideas about exactly what you wish to do with data science, then project-based learning can be a great way to achieve what you want.
Also, as a professional, you may be very short on time and need something that you can quickly add to your portfolio in order to apply for better jobs, in which case, project-based learning helps achieve faster results.
Wrapping Up
Now that you know, assess yourself in terms of how much time you have, what results you are after and how much you already know about data science. Knowing that will help you better figure out which mode of learning is best suited to your learning style and goals.
