Why Datacamp Is Probably The Best Learning Platform For You
Kickstart your learning with Datacamp. Sharing my 1-year Data Science learning journey on the platform.
It’s been more than a year since I decided to pursue learning again and make a transition to the field of Data Science. In the beginning, the long list of knowledge of subjects, technology and tools baffled me. I needed to improve on my Python, and SQL programming. Also, to revise the high-school statistics concepts, learn and apply Machine learning algorithms. This was the bare minimum to get hands-on experience and an entry/mid-level Data Science job.
It was relatively easier for me to ramp up my programming skills as I had worked on Python and SQL before. However, It was a tough task for learning algebra, statistics, and Machine learning. I explored the whole internet for quality content. I took many online courses and enrolled in different live sessions. Links to articles, journals and websites cluttered my browser’s entire bookmark bar.
In this entire process, I realised, that referring to more resources, became even more difficult to keep track of my learning and progress. It was confusing to keep up with different terminologies and methods used across these courses.
In a way, it turned out to be more counterproductive than what I had intended.
Don’t give your students a stretched out spring - @merott
A year back, when I was spending most of my time learning online, I used to come across advertisements for new courses and certifications. It was the time (and even today too) when many SMEs, industry leaders, and tech companies were rolling out their new Data Science courses and programs.
The majority of these online courses have more or less the same depth of content. It’s the structure and timeline of the course and content that makes the real difference and improves the consumption quality.
One fine day I came across a new ed-tech company that was advertising their brand new data science learning platform. Intrigued by the creative logo and advertisement I went to their site to check if it was for real or just another click-bait. In my initial expression, I genuinely liked the overall structure of the courses and the look and feel of the platform built by Datacamp.
But how exactly is Datacamp different from the rest of the platforms?
Datacamp has a very effective structure in place. It comprises four important segments as below:
- Learning:
This has all the courses on a wide range of topics including Python, SQL, Statistics, PowerBI and so on. - Practice:
In the practice section, there are quick quizzes of 5 questions with no time limit. - Assessment:
Assessment is a time-bound test with 15 questions. Upon completion Datacamp lets you know your strong and weak areas and suggests the relevant courses for improvement. - Application:
In application, there is a range of projects and case studies with datasets of different domains and industries.
It is a well-known fact that learning alone doesn’t help to master a subject, tool or skill. It is when you practice and apply the learnings to reinforce the concepts, and techniques and identify the areas of improvement.
This structure of Datacamp creates a cycle of learning the concepts, practising them, assessing the knowledge frequently and applying the learnings to a project to test the real-world challenges. Thus, it offers a 360-degree approach to gaining mastery of a topic or tool.
Learning
For someone who works full time, it’s quite challenging to enrol on a course which demands 10–12 hours per week. Datacamp has split the content into mini-courses of 3–4 hours and these mini-courses are further split into multiple chapters. This works! especially when it’s really difficult to get started, it eases the process, thus you can schedule your time for learning and practice accordingly.
One good to-have feature is you can maintain a streak, this creates a mental hook and inspires you to not skip the day for learning.
Learning Tracks:
Datacamp offers different learning tracks like ‘Data Analyst with PowerBI’, ‘Data Scientist with Python’, etc. In a learning track, all the required courses and projects are thoughtfully clubbed together. The courses are put together such that the essentials are kept first then intermediate and last the difficult topics. Nevertheless, it is up to the user to choose and complete the required courses.
Datacamp issues a completion certificate if you complete all the courses and projects in that learning track.
Workspace:
Datacamp has recently rolled out a new feature of online workspaces. Workspace is an online IDE for coding Python, SQL and other programming languages. Users can create and run juypter notebooks, share them with co-learners and document them for others users.
Datacamp also provides coding templates. Users can readily use a commonly used piece of code such as building a K-Means model or code for getting metrics of classifications.
The platform also provides users access to cheatsheets on all the Python, SQL, Statistics and Machine learning-related topics.
Live Events:
It’s not about just courses and projects. Datacamp organises many live events on different topics. You get to listen to subject matter expertise and industry leaders and their perspectives.
These events are not only on technical topics but also on how to learn and grow in the field of data science.
You can register for these events in advance and you will receive the invites to your calendar.
My jouney on Datacamp
I decided to take the Datacamp membership after thinking for a week. I started with Python and SQL and practised a lot on the basics. It covered everything on Pandas, NumPy and visualization libraries.
Then I moved my focus to supervised machine learning algorithms. I worked on multiple regression and classification problems. After getting the confidence and pace I started working on unsupervised machine learning algorithms and other important techniques such as PCA, Class imbalance and model tuning.
Every day, I used to start my day with a practice session (to get the daily XP so that I can maintain my streak 🙏) and then start with the course. on weekend I would either work on a project or go through PowerBI sessions.
So far I have completed multiple courses, assessments and a few projects that were closely related to the domain and industry of my interest. Currently, I’m about to complete the Data Scientist with Python track.
https://www.datacamp.com/profile/GaikwadChinmay
My Datacamp profile:
Indeed, my learning journey does not and will not stop here. Thankfully, I got a good start and a platform that works for me, now there is more to go!
If you find this article helpful please share it with your friends, co-learners and colleagues, kindly share your feedback in case of any questions or differences in opinions.
*This article is not sponsored by Datacamp, the views expressed are entirely based on my experience*
