5 Essential Tips to Choose The Right Data Science Learning Resources

3 min readOct 8, 2021

A beginner’s Guide by Learnbay

Data science learning resources are flooding everywhere. Unfortunately, such massive availability of online courses, practice websites, competition sites, and e-books can easily puzzle you to choose the wrong one. So, to make your data science career transition mistake-proof from learning resources, I have developed five professional pieces of advice for you.

Let’s see what those are.

1. Choose a Course that offers Interactive Learning Mode and end-to-end career transition support.

Recorded sessions are the best option for brushed up learning. While you are learning from scratch, then the model of learning has to be interactive fast. Such a session usually is not available for free. You need to pay for that. So, before finalising a paid data science learning course, ensure if it provides complete career transition assistance or not. Assess for the following.

● Live online classes/ offline classes

● Domain-specific Hands-on industrial project experience

● Capstone project opportunity

● Job assistance with interview questions and mock interviews.

● Domain-specific Internship (added advantage)

● Life-long access for course modules and recording of classes.

2. Choose tools training resource that supports your domain expertise

Opting for an additional online resource for practising the knowledge of your learned data science tool is fine. But be assured you are

● Learning and Practising the right tool

● assessing the latest version of each tool

● Following guidelines and techniques for the tools are on-demand in your industrial domain.

● Learning the best-fit usage strategies currently available.

3. Keep your focus on learning modules.

To gain the maximum possible benefits of a learning resource, check if the associated learning modules are

● Focused on your domain expertise.

● Focused on your level of working experience.

● Highly competent with the current job market demand.

● Offer you the scopes of learning from scratch.

● Includes all the theoretical concepts, practical tools, and soft skill development opportunities for a sustainable data science career transition within your domain.

4. For projects, cross-check data resource reliability.

Finding a large amount of data set is quite easy but finding the right one is not easy. With the massive development of IoT, the exposure of data sets is now expanding, but that also expands the reliability concern. Before inserting data set in your project, ensure it’s

● free from legal hazards

● Cross-verified

● Bug-free

● Up-to-date

● Authenticated

● Original

Better to verify the datasets from multiple resource platforms.

5. For e-books, tutorial videos, technical blogs, — choose the updated one only.

Listening to blogs, streaming youtube videos, and reading e-books are the best strategy for on-the-go continued learning in our busy lifestyle. But stick to such resource only that are

● Regularly updated

● Updated for tech tool’s new features, bug fixations, etc.

● Republished or launched with latest conceptual and informative updates (for the book/ blogs)

Mater Advice

Whatever resource you choose, it should always provide you with an in-depth idea, not the cheatsheet one. Besides, the resource has to be acceptable enough to become a smart but knowledgeable data scientist rather than hardworking.

The best strategy is to choose such a resource that offers ample opportunities for dealing with practice problems.

You can confidently opt for Learnaby data science and AI courses for a comprehensive and full-proof online data science certification course. Once you register for the Learbay data science course, you’ll get rid of all headaches about domain-based learning module search, finding reliable data sets for industrial projects, Hunting for creditable internship resources, searching for e-book references, etc. The data courses by Learnbay provide a complete package of the solution to all of your data science learning needs.