Probably, this question is the most important when it comes to selecting an analytics course. Like we keep mentioning, analytics requires an immersive learning experience. The learning curve in data science courses is incremental, meaning, the learning of the concepts, tools and techniques is a gradual incline starting from the basics to more complex algorithms. You will also be working on capstone projects and be exposed to industry experience, through which you might feel that the physical presence of people involved in data science would help.
However, dedicating time and finding an ideal institute that offers you the best analytics program is quite a concern as well. To help you make a clear decision, we have broken down the distinct aspects and pros of each – online training and offline training. This will help you get a clear idea of what your requirements are and how it would work for you individually.
Online analytics training works best for those who can dedicate only a couple of hours of their time studying analytics. Most of their time gets spent on their commute to work or at work and it often happens to them that they have to miss most of their classes and catch up with the recordings. The recordings are the biggest advantages offered by online training sessions. It is self-paced. Besides, you also get access to student and teachers portals, where you can post your questions anytime and get ideal solutions and answers to your question on analytics topics.
Online training works best for students who have disciplined temperaments and would like to build their own study schedules. It also works best for professionals who have rigorous and inflexible working commitments and who might not be able to set aside a predetermined time and date for classes.
Although this may be more traditional, this has a fair number of advantages. The first advantage is that you are physically present in a classroom with professors and other data science aspirants. This involuntarily makes you competitive and more committed to your course. Self-paced learning is good but you might lose the pace of learning if you happen to miss a week or two and then catching up becomes difficult. In physical classes, you are more accountable for learning.
Classroom training also helps you to consistently understand where you stand among your peers and keep evolving as a data scientist aspirant. If you’re feeling you need to catch up to the pace of others, you would automatically see yourself working on projects, experiments or online resources to step up your game.
It also works for professionals who can commit fixed time and date slots for classes during weekends. It’s ideal for those who usually have preset learning goals or have a fixed time during which they want to finish the program. Students who also feel that they benefit from more extended access to faculty also prefer this kind of program.
The reason for choosing one or the other depends on individual requirements and learning needs. But if you are looking for expert comprehensive in-person training, the Full Stack Data Science Bootcamp from Jigsaw Academy is an ideal solution to learn analytics in person. We conduct weekend classes for a duration of 6 months. If you’re a serious aspirant, we are sure this course will make you job-ready in just 12 weeks. Know more about the bootcamp program here.