What is Data Science?
Why do I need to learn Data Science?
How do I learn Data Science?
These are probably the most frequent questions I have heard from my Students & participants from various training programs I have conducted. Time & again, I have always tried my best to explain the same to all in the most simple approach possible. Which is what I am aiming to achieve through this blog post.
What is Data Science?Let us try to demystify this question first
Data Science is the amalgamation of information(data), domain knowledge, technology, machine learning & data visualization. Using all these, one tries to create an optimal formula to derive actionable insights for each Business Scenario.
In all its simplicity, Data Science is the tool one leverages to better understand a situation and take appropriate actions if necessary. For example, let us take the example of a Company like us Digital Tesseract.
We are currently in the process of hiring Interns and Part Time contributors to our Organization. In order to attract the best of talent, we are striving hard to find ways to shortlist the best profiles from a very long and exhaustive list of potential aplicants.
Here, Data Science could help us sort our applicants for suitable vacancies that we currently have. We are currently collecting information from all our applicants using a simple form. In that form we have various data points that we are collecting such as personal bio, interests, experience and so on. This data is helping us understand our applicants beautifully and categorize them easily. See below one of the metrics that helps us understand.
Imagine, if we hadn’t used this questionnaire and simply collected resumes of all applicant! We would have simply wasted hours trying to find and categorize the right candidates.
Data Science is all about finding ways to make data work for you. You try to make sense of information and take informed decisions.
It is not necessarily simple all the time like our above example. Data Science could also use a complex set of methods or techniques to demystify questions using data? For example, Data Scientists & Medical Researchers around the world are now trying to figure out various insights and cures for the most dangerous pandemic (COVID-19) which is raging throughout the World right now. There are multiple activities going around the world such as trying to,
- Predict the speed of the disease spreading in each Country/Region
- Develop drugs that can cure the disease efficiently
- Forecast the next pandemic (Whether there might be a second or a third wave of attack
- and many more
Whether the steps taken to find a solution are simple or complex, it all falls under the category of Data Science. Applying suitable techniques from machine learning, AI & NLP areas using tools/programming languages like Python, R and SAS and finally making sense of the output using the domain knowledge for an Industry is what we need out of Data Science generally.
Why do I need to learn Data Science?Advancing to the next question
In today’s fast paced World, data is collected by each and every Organization to better understand their Customers, Employees and much more. The challenge however does not lie in collecting this data, but deriving meaning and sense out of the same.
Enter Data Science. it is almost impossible for many companies to understand their data without applying some transformation or technique as the Raw data sometimes is just huge in size or is highly unclean. For example, when you ask a Customer to write a review about their satisfaction with the product you sold them, we might have to mine for keywords such as “Excellent”, “Happy”, “Good” within their lengthy paragraph of a reply. This for instance can be solved using a set of Machine Learning techniques called NLP(or Natural Language Processing).
What is the need to apply all these techniques to understand more about your Business? Of course, the simple answer is to monetize from these insights and also to ensure better services to your Customers.
It is not necessary for every individual to be a Data Analyst or a Data Scientist today. However, knowing Data Science always gives you an edge over others in the same Business. Twenty, or Thirty years back, many Industries(Not all) relied purely on Subject matter Experts in their Companies to help them with taken better decisions. Now, although there are still SME’s present in various Industries they still need the right tools to understand the huge amounts of data first.
So, whether you are an Artist or an IT professional, it is now safe to say that being Data driven in your decision making would probably give you a winning edge over your competitors in the long run.
How do I learn Data Science?And the final question to tackle
There are hundreds of ways to learn Data Science today. One search in Google for the keyword “Data Science Courses” or “Data Science Free tutorials” will now throw thousands of helpful learning resources for us. However, skimming through them and selecting the right channels is always a tough choice. So, we have compiled a very short, but sweet list of Resources which can be utilized by you for starting your journey in Data Science.
Free Learning Resources
- Introduction to Computational Thinking and Data Science – An MIT OpenCourse
- Learning from Data – From Caltech University
- Machine Learning Crash Course – From Google
- Machine Learning with Python – From IBM’s cognitiveclass.ai
For Intermediates & Experts
- Practical Deep Learning for Coders – From fast.ai
- Natural Language Processing – A Free Learning course @ Coursera
- Natural Language Processing – From Carnegie Mellon University
- Deep Reinforcement learning – From UC Berkeley
And of course, I would always recommend you to follow us on Youtube and other social channels to regularly receive free learning resources curated for Data Science practitioners, enthusiasts and learners. The links are given below for you.
Alternatively, you could sign up with us for a free account and receive Free & Paid Courses. Find our Login/ Signup option in our Homepage Here.
A big thanks to all those who read this post. Let us know your thoughts below or simply give us a thumbs up by sharing our post in one of your preferred Social Networks.
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