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A complete beginner’s guide to Data Science

Data Science: A Brief Introduction-

Facial recognition, Speech pattern recognition, Fingerprint recognition, Retina Scans are all modern tools to make us happy. Online Price Comparison, Airline Ticket booking, Movie ticket booking, Calculation of time taken, etc. are some fancy modern tech to help us live. But, have you ever thought, how do they work?

Yes, they are what we call data science or rather big data handling. These are some of the few notable uses of data science. Data Science generally refers to extracting meaningful data from lots and lots of data. Nowadays, data science has progressed a lot and helps develop our technology as we know it.

Future of Data Science-

Self-driving cars to humanoid robots, everything will need the help of data science to work. Since the data that is being stored on the servers is overflowing, new technologies like clouds have been developed to overcome that problem. The data in its raw unprocessed form is of no use to us. This is how data science will help us to sort and filter the data according to our use and need.

What does Data Science include?

Data Scientists are expert in the field of mathematics, programming and should have analytical thinking skills. Since Data Science is a very widespread topic. People nowadays focus on specific parts of it like – Machine Learning, Deep Learning, Neural Networks, Data Mining, Forecasting Analytics, etc.

  • Machine Learning – Uses data science to understand and improvise how machines treat and understand data.
  • Deep Learning – The process of making a computer or a program to develop autonomous decision-making skills.
  • Neural Networks – Programming a computer to think and behave like a human.
  • Data Mining – Searching and sorting related data from clouds.
  • Forecasting Analytics – Prediction of certain things by viewing past records.

Importance of data science:

Here are a few reasons why data science is so lucrative and is gaining importance nowadays-

  • Data Science helps companies satisfy customers. The sole reason why companies like YouTube and Amazon have such high brand value is that they satisfy their users and customers, which obviously is done through Data Science.
  • Usage of data science across all fields. This is completely true. Nowadays data science or big data is very crucial to all aspects of our life.
  • Helps government organizations identify frauds present in the market.

Challenges faced by Data scientists-

Although data science is a lucrative and promising field, it also faces challenges that need to be overcome. Some of the challenges are-

  • Dirty or corrupted data – Over 30% of the data available on the servers are corrupted or outdated. This poses a big threat because it tends to complicate the process of data mining.
  • Lack of talent – This broad field needs new faces and brains to overcome the drawbacks of lack of workforce.
  • Inaccessible and classified data – These types of data comprise of about 11% of the server capacity. These data cannot be accessed by general people, thus making it inaccessible.

These are a few problems faced by data scientists all over the world.

Resource Box-

If you are a competitive programmer and excel at mathematics than data science might be an answer to your quest. These top  data science courses in Pune will surely help you to bolster your position as a competitive data scientist and usher you to a new world.

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