Considering the fast paced development in the world of Data Science his words are likely to become true. We live in the age of information and it’s quite usual to get overwhelmed with the amount of data we process each day, both in our professional and personal lives. The Internet these days is full of buzzwords related to machine learning, artificial intelligence, deep learning and the Internet of Things. Have you been wondering, if you can really make use of all these techniques in real life? Do you wish to begin your data science journey too? Then read this article to know where you can begin as a new bee!
Bill Gates once said, “A breakthrough in machine learning would be worth ten Microsofts”
Data Science Journey is based on the foundation of mathematical and statistical concepts which are universally applicable to all the sciences. That is the reason why data science is not limited to any specific field of study. It finds applications in numerous fields such as Healthcare, Food and Beverages, Petrochemicals, Agriculture, Defence and Space. To back these claims, let’s take a look at some common applications of artificial intelligence and machine learning in above mentioned fields:
| Field Name | Common Applications |
| Healthcare | Classification and Quantification of raw materials: Non-destructive testing of raw materials using spectroscopic sensors like IR, NIR, Raman etc.Distinguish between materials: Innovator Vs. Generic ProductDrug Discovery: Quantitative Structure Activity Relationship, Molecular modellingGenomics: Personalised medicines or dietMedical diagnosis: Cancer PredictionMaterial selection: Composition of materials that results in desired quality |
| Food and Beverages | Automating sensory evaluation of productsClassification and Quantification of raw material: Identifying the source of raw materials and nutritional profile of the material (% of carbohydrate, fat and protein)Similarity between materials:Identifying substitute for an ingredientMaterial selection: Composition of materials that results in desired qualityShelf life: When is the product likely to degrade |
| Petrochemicals | Classification and Quantification of raw materials: Non-destructive testing of raw materials using spectroscopic sensors like IR, NIR, Raman etc. |
| Agriculture | Better crop yield: Identifying seeds with superior qualityCrop quality/ harvesting: Is it best time to harvest crop Shelf life: Predicting shelf life of harvested cropSoil texture using sensors |
| Defence and Space | Material selection: Composition of materials that results in desired qualitySpace exploration: Is there water on mars? |
I am sure you must have gotten interested in this new age Mantra and be wondering will this be applicable to you and how?
To know this let’s begin by answering below questions:
- Are you dealing with large sets of data that do not make real sense to the human eye?
- Are you currently using some tools to sort and analyze your data but still struggling and thus looking for a viable alternative?
- Have you been told that the buzzwords of machine learning, artificial intelligence or the Internet of Things could solve a problem that you are faced with today?
- Are you very much fascinated by this new avenue seen all over the internet, but taking the first steps seem too daunting to make any real progress?
- Do you believe that, trust is good but evidence is better?
If you answered yes for any of the above questions, then yes, Data Science Journey is for you! Peter Sondergaard has once famously said that, ‘“Information is the oil of the 21st century, and analytics is the combustion engine”.
The best part is that anyone can use the data science techniques and benefit from them. You need not have to be a coder or an expert mathematician. Various software tools have been developed by experts in the field which can be purchased as per your requirements.
Our cloud-based DataPandit software solutions is one such simple and user friendly interface developed by Let’s Excel Analytics Solutions.These softwares enable you to get appropriate insights out of your data and lead you in the right direction.
Data science can be learnt not just with theory but with hands-on experience. It can be said that Data Science is a habit, not a skill. The more you practice it, the stronger you get.
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