Looking for a Data Science free online course?
Becoming a Data Scientist doesn’t always require a fancy degree from a reputed institution. You can get started on your way to becoming a Data Scientist without anyone’s help, literally!
Let’s understand Data Science first, shall we?
Data Science uses Data to uncover patterns, relationships and behavior that may impact business decisions.
Optimum use of Data Science in business has encouraged better customer service, inventory management, targeted advertising and many other profitable business decisions across industries.
Can I learn Data Science on my own?
Yes, you can absolutely learn Data Science on your own! A Data Science free online course is nothing but acing these three spheres:
- Coding with Python
- Math and Statistics
- Domain Expertise
As daunting as this might sound right now, let me explain how you can target this successfully in a few months.
How do I get started with Data Science?
Before you jump right into the tidal wave that is Data Science, you need to be aware of what’s happening in the space.
I’d suggest starting small. Look up free YouTube videos, start following blogs and Data Scientists on social media.
Here are some ways to go about it:
- Many informative YouTube channels will help you get started. You can start to learn Data Science for free through videos and podcasts.
- The next step would be to follow influential Data Scientists and AI experts in this space. You should check out blogs and articles in this space.
- Clear all possible doubts about the field by reading different books authored on Data Science and related subjects. You can find a list here.
Where do I get a Data Science free online course?
Now that you’re all set to understand the scope of Data Science and it’s contributions to the world, you should dive a little deeper and get started with the basics.
Start with Coding
You should get started with some basic coding to amp things up. Pick a programming tool to aid your Data Science learning. Here are some popular options to learn from:
It reads like plain English and already has a number of powerful, feature-rich libraries you can easily use and save on a lot of coding time. Since Python is free to use and learn, you can try your hand here for free lessons.
R is yet another free-to-use programming tool for the community. It is popular among academia and research enthusiasts.
Although R requires longer codes to be written than Python, it isn’t a hard language to learn.
You can start with your R learning here.
We would also recommend SAS as a programming tool but it is not free to learn and not enough machine learning-friendly to be your best pick.
Before you move to other aspects of Data Science, you should solidify your coding skills, Try competing on these platforms for a headstart:
Build Math and Statistics Skills
The best way to work on your Math and Stats capabilities is to read a book. Literally!
You will require a working knowledge of linear algebra, calculus and probability to make a breakthrough in the space. A lot of Machine Learning algorithms are based on mathematical and statistical concepts.
There are a number of books available for your successful transition in Data Science. Here is a list you might want to check out:
- Probability: For the Enthusiastic Beginner
Author: David Morin
- Think Bayes
Author: Allen B. Downey
Author: Allen B. Downey
The Elements of Statistical Learning: Data Mining, Inference & Prediction
Authors: Trevor Hastie. Robert Tibshirani and Jerome Friedman
Machine Learning – A Probabilistic Perspective
Author: Kevin P. Murphy
This is something you develop at your workplace. Learning new and new technical skills is a waste if you can’t put things in perspective.
Remember a Data Scientist’s major responsibility is to solve business problems. Business problems aren’t always clear as day.
A Data Science free online course will get you nowhere unless you have reliable domain expertise.
Improving a business process, cutting down on turnaround time, cutting down on costs, enhancing productivity or improving profits is not always a straightforward solution to a given problem.
Many times as a Data Scientist you need to figure out whether a problem exists before you go about hunting down solutions for it. That kind of approach can’t be developed with a myopic idea of how the business works.
In your current role, go beyond your regular job profile to understand business issues and areas of improvement. Depending on the sector or industry you work, the application of Data Science might be different.
This is how you get a combined exposure to all 3 variables affecting your Data Science education. You might want to check out another helpful link for your journey.
After completing your Data Science free online course, you will understand that learning Data Science is a continuous process and there are many things you need to work on simultaneously to improve your standing.
Build a strong network of peers. Using open-source tools will give you access to a strong community anyway. Make good use of such connections.
Practice on data-sets through Kaggle. Upload your projects on GitHub and make sure to check out other people’s projects as well.
Remember to use LinkedIn and relevant social media to expand your horizons about Data Science.
Practice Machine learning Projects!
Another way to improve as a Data Scientist is to undertake as many Machine Projects as possible!
Work on random data-sets and deploy Machine Learning models to test and identify patterns from your data.
You can read more about how to deal with a Machine Learning Project, here!
Do remember a Data Science free online course will cover basics and help you get started in the right direction. There are, however, a number of things you must do in order to survive as a Data Scientist.
To become a seasoned Data Scientist, you need to go through guided training from a reputed institute to get your work cut out for you.
INSAID offers 3 well-structured courses in Data Science, Certificate in Data Science Foundation, Global Certificate in Data Science, and Global Certificate in Data Science and Artificial Intelligence.
To know more, talk to our Admissions Team at firstname.lastname@example.org.