How Online Education In Data Science Helps Students To Become Work-Ready Graduates

How Online Education In Data Science Helps Students To Become Work-Ready Graduates

Data science is a relatively new field, but it has become central in all spheres of human activity. So, why the ongoing buzz around data science? 

According to reports from IDC, the global ‘datasphere’ will expand to 175 Zettabytes by 2025. Now, that’s a lot of data.

But, to get the best out of the gathered information, you need certified experts with technical knowledge — these people are called data scientists.

For those looking to branch into this field, let’s check out how you can make a career as a data scientist. We will also review some data scientist jobs. 

Why is data science relevant today?

Data science combines statistics, analytics, artificial intelligence, machine learning, and computer science into an all-encompassing discipline. 

With the growing mass of data in the world, every industry needs data engineers and specialists. 

Here are various fields that look towards data science solutions:

  • Healthcare

Hospitals and healthcare professionals need data management tools to track patient information and outbreaks. From the experiences with the COVID pandemic, data science jobs in healthcare have become more vital than ever.

  • Business

Companies can use big data initiatives to monitor and evaluate product and employee performances. The results from these evaluations enhance decision-making processes, spending, and recruitment.

  • Politics

Politicians, campaign managers, and political analysts need data projections to get an accurate read on their electorate. They can also use data science software to predict voter behavior.

  • Transportation

Smart cities and megalopolises now use big data to plan transportation networks in an effort to decrease traffic and congestion.

  • Marketing

With the use of data science in marketing, companies can identify their target audience faster and reduce the cost of advertising. 

  • Information technology

Data scientist jobs are opening up in IT at a rapid pace because the market craves data-driven innovations. 

What does a data scientist do? 

On the surface level, a data scientist collects and interprets data. But, this definition doesn’t even cover half of what they do.

Firstly, a data scientist must define, undertake, and execute a fact-finding mission to identify information sources. Afterward, they have to sort the data according to purpose and relevance. This also involves creating silos for data storage.

Eventually, they can create a data analysis model for further evaluation. Alternatively, the data scientist can use a pre-existing model or a data management system. Then, they have to deploy the model and generate results. This completes the data analysis cycle. 

What skills must a data scientist have?

How Online Education In Data Science Helps Students To Become Work-Ready Graduates

 

(https://images.pexels.com/photos/7688559/pexels-photo-7688559.jpeg?cs=srgb&dl=pexels-yaroslav-shuraev-7688559.jpg&fm=jpg)

This technician is installing monitors in a data center.

Working with data requires a lot of attention to detail. If you want to land high-paying data scientist jobs, here are the must-have skills. 

  1. Problem-solving skills

A data scientist must be a good problem solver. Think of your work as having a jar of Skittles: you have to sort them by color without spending too much time and resources. With advanced problem-solving skills, you can optimize the process.

  1. Data acquisition skills

Sometimes, data scientists work with established databases. But, in other cases, these specialists have to scour the entire datasphere to pinpoint relevant data for a specific initiative. 

  1. Analytical skills

Every data scientist must be an excellent data analyst. You need an in-depth understanding of statistical analysis and mathematics in order to interpret large swathes of data. 

  1. Programming skills

Programming skills differentiate data scientists from data analysts. The science aspect involves the use of programming solutions to optimize data management processes. Besides, a significant part of your work as a data scientist will include working with algorithms and digital computations.

  1. Machine learning experience

Knowledge of machine learning principles will help you avoid many data science pitfalls. Besides, machine learning and artificial intelligence are now integral to data initiatives in every industry.

  1. Database understanding

In your work as a data scientist, you won’t spend much time with spreadsheets. Most of your data will come from database extractions. So, you need to study SQL since you will be working with MySQL, Oracle, and MongoDB. 

Can you become a data scientist without a university degree? 

You can land entry-level data science jobs without a degree from any university. Like most jobs in IT, the applicant needs to display proficiency in the field rather than a university diploma. At the same time, data scientist jobs are in high demand, and the supply is limited; therefore, companies are willing to hire promising talent and train them internally.

In addition, companies like Google now offer data science and analytics courses, which bear more weight than college certificates. Even online learning platforms like Coursera and LinkedIn learning can help you take your first steps in data science.

So, all you need to become a data scientist today is to find an accredited online course and start honing your skills. People with a math or statistics background also have a massive advantage in this regard.

Final Words

Data science is the future of humanity. So, forging a career path in this field makes sense: you can even follow a data science path related to your passion. But, before you take this leap, ensure that you have the required skills. Work on your technical skills and apply for online courses to patch up your lack of required technical knowledge. Even if you don’t have the time to attend a university, you can gain an online certificate from Google or Coursera.

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