Overview of Data Science 

We are all generating data every day since we were born. 

Which school did I go to? which restaurant did I eat at yesterday? how did I rate it? what was my last vacation spot? How often do I post pictures of myself? - Every answer to these questions is some form of information that can be stored as data. That is how it starts and as we share more and more, we contribute more to the data ecosystems. Some might feel scared as by sharing these, we are probably exposing ourselves. 

Same time, because some of us shared our opinions, we have the possibility to know- how reliable is the school/hospital next to my home. Which are the best visiting places in the city? Tasty pizzas around you? Best bars? So, sharing data is not a problem but whom we are sharing with ,and of course, strict data protection laws are important.

In most cases, we are the data, and data science is an attempt to make informed decisions, bring transparency, and ultimately, try to understand ourselves better. Therefore, it should not remain only for organizations making more business, profits, and acquiring more customers. 

It should have a presence in our day-to-day lives and make a positive impact - we all should learn a bit of it to progress and harness its benefits of it.

Data Science (DS) has progressed a lot in the last 10 years. Nowadays, digitization has been part of our social upliftment and DS is contributing majorly to the same. Let us check some applications:

Education

With the advancement of computers and the internet, students are learning through educational apps at their own pace and comfort. They are tracking their progress and getting instant feedback. Also, a student can choose teachers based on the ratings of other students.

• Real-time interaction with fellow students.

• Feedback system to measure performance.

• Gamification of learning to help students progress fast.

Healthcare

Data Science can be used in improving diagnosis, and medical research, and reduce costs. More than 5% of patients in the US are misdiagnosed every year - more than 15 million. Analysis of breathing patterns and heart rate can uncover many insights into the health conditions of patients. 

• Sleep patterns, breathing rates, and heartbeat analysis can be used to provide safeguards from future disorders.

• Diagnosing patients during COVID by using digital platforms and providing further analysis.

•  Medical research using high-performance computing and images.

•  Tracking individual patient history to provide effective personalized treatment.

Banking 

Banks are common targets of hackers to steal money. Although fraud detection algorithms are one of the top priorities, there are more areas in banks that are using DS-

•  Customer management and educating existing customers with banking products.

•  Acquiring new customers through proper marketing

•  AI-enabled customer support to reduce operations costs

•  Financial modeling and research 

•  Credit scoring or Schufa check helps customers and banks to decide on loans.

There is a bit of data science in every field - E-commerce, Retail, Aviation, Transportation, Climate change, Energy, Media & Entertainment, and you just name it. 

There are numerous ways to learn data science. A most common start is to know the basics of tools and choose a programming language. 

There are a few tips for beginners.

• Read articles and educate yourself on the trends.

• Start a plan of your own and put some feasible targets.

• Learn a Programming language. Python is popular and beginner-friendly and anyone without a background can start learning.

• Take a dataset and apply your skills.

• Make some conclusions and measure your results.

• Improve.

If you are stuck, take some professional help to get started. Once you start and become part of the ecosystem, the learning opportunities are infinite.