Things to think about while choosing a data science course

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New Delhi : The increasing digitization of the world has led to about 2.5 quintillion bytes of data being created on a daily basis. This figure has accelerated further since it was last counted and is projected to continue growing at a fast pace in the future. But without being able to mine valuable insights from this data, it amounts to nothing. And who but data scientists to skillfully manoeuvre through all the data to arrive at actionable solutions.

Data Scientists are becoming increasingly indispensable to organizations and is emerging as a very sought-after career. If you love problem-solving, computing and handling large amounts of data, then a data science course can help you build a successful career for yourself.

Is it worth doing a data science course?

The answer is yes. Right from the Finance & Marketing industries to Pharma companies and Banks, data science is so widely adopted that IBM predicts that the demand for data scientists will soar by 28% in 2020 alone.

The average salary of around INR 9,00,000 per annum in India makes it one of the most well-paying jobs with a number of promising opportunities in 2021.

Source: Glassdoor

Businesses rely on data scientists to make evidence-based decisions and make sense of the large amounts of data that is available. Often this involves understanding customers and their behaviours and even helping predict future markets.

Data Scientists help companies –

A. Make data-driven decisions

Data collected is often scattered and needs interpretation. Data scientists usually research the data at hand and use predictive analytical tools to gain insight on the data. Facebook uses data extensively to target specific ads to users who are more likely to find it relevant. Based on past clicking behaviour and interests, Facebook accurately predicts your interests and likelihood of consuming certain products and services.

By recording relevant metrics, businesses can make informed decisions on all aspects of the organization. They can reduce trial and error and make confident decisions based on established patterns.

B. Help improve product relevance an identify right audience

Data scientists help analyze the market to access the relevance of products and understand their customers. By constantly analyzing the needs of customers, data scientists help make products more customer-oriented and help business teams identify which audiences they must target for maximum impact.

C. Help in recruiting and training

Data science can also help establish dedicated databases for new recruits to store job-related information and identify potential employees instantly. Data scientists can help mine through job applications to pick out only the most qualified candidates. They also document their insights helping teams across the organization to learn more about the business.

While this is only some of the top line use-cases of data science in businesses, their roles are far more intricate and crucial. Making it one among the most beneficial courses to pursue in the country. 

Below are some of the factors you must consider before you enroll to learn data science.

1.  Ensure practical sessions are included

Find a course that not only covers the theoretical aspects of the concept but also includes practical sessions for a holistic learning experience. It is essential to practice concepts you’re learning throughout the way to pick up on skills faster.

Springboard’s data science career track offers a chance to build a professional portfolio by completing 14 real-life projects, including two industry-worthy capstone projects to showcase your skills to employers.

2.  Consider the experience of the Trainer

While choosing the course consider the professional background of trainers. Learn data science from trainers who have proven experience in their field. Their first-hand experience will help you understand concepts in detail and will also help you understand how projects are executed in organizations.

At Springboard's data science career track, our world-class mentors are hand-picked for their experience. Our mentors have worked with organizations like InMobi, Mahindra, and RedHat to name a few. They also offer personalized mentoring to ensure the learning experience is more valuable.

3.  Evaluate Placement Reviews

It is essential that at the end of your data science course, you are adequately prepared to begin your career. Courses should help you not only develop job-ready skills but also help you with your data science career.

Review placement histories to access the kind of jobs previous students have landed. Evaluate the types of organizations and the pay scale offered to make a more informed decision. At Springboard, our courses come with additional career coaching that involves

•         Creating a successful job search strategy

•         Building your data science network

•         Finding the right job titles and companies

•         Crafting a data science resume and LinkedIn profile

•         Tips to ace job interviews

•         Tips to negotiate your salary

4.  Speak to past students

The easiest way to decide on a course is to speak to students who have pursued the course. Speak to them about their experience and ask if they’d recommend the course. Interaction with the past students will also help you understand what to expect during the course and help you prepare accordingly.

Springboard’s courses come with a job guarantee that all our students can vouch for. Srinidhi Muthu, currently a Data Scientist at Caterpillar says, “Springboard really helped me to start using data science skills that help me find a more relevant full-time Data Science role.”

Now that you know what to look out for, choose an online course that offers you a chance to begin your data science career. Springboard’s data science course helps you master foundations of data science and even help you choose your focus area: advanced machine learning, natural language processing, or deep learning.

The course offers you the opportunity to build a professional portfolio by completing 14 real-life projects, including two industry-worthy capstone projects to showcase your skills to employers. The course comes with a personalized 1:1 mentoring and a job guarantee. You can check out the details of the course and its curriculum in detail on Springboard’s Data Science Career Track page.