Introduction

Data science has been the most sought-after job for more than five years, and demand is only growing. According to the "The Humans of Data Science" research from Michael Page India, a worldwide recruitment business, 11.5 million new jobs will be available in the field by 2026. LinkedIn's Emerging Jobs Report shows that the worldwide data science market is expected to rise to $230.80 billion by 2026.

Although the data science industry is expanding exponentially and adding millions of new opportunities, many data science aspirants who have earned solid data science skills still need help to land their first position in the industry. This is mostly because they lack the practical skills necessary to apply data science to produce business value.

In this article, we'll examine the various aspects of data science job preparedness and how internships play a crucial part.

Data science Internships

Internships in data science are fantastic possibilities. Comparatively speaking, getting a data science internship is much simpler than getting a job. Although you will only receive a tiny stipend for your efforts, the internship will allow you to work on actual projects and hone your technical skills.

Potential Benefits Offered by Data Science Internship

Exposure to Real-world application 

An internship is a fantastic way to gain experience working on real-world projects and connecting with clients.

Timing flexibility

Since most employers won't anticipate an internship to fill a full delivery job, you can use the downtime to concentrate on acquiring new skills in addition to your internship duties.

Practicing technical Skills

The learning phase's capstone project uses learning data, which can be used in internships to practice technical skills and comprehend the difference between learning data and real-world data.

Responsibilities and roles

Understand the many roles involved, their duties, and how data science initiatives are carried out.

Communication with stakeholders

Numerous teams, including business analysts, subject matter experts, customers, or other business stakeholders, are involved in data science projects. One of the essential skills that may be acquired during the internship is effective communication.

Make connections with business leaders

Through project interactions and networking, internships assist in establishing connections with senior industry executives. This might be quite helpful while you pursue your profession.

Obtain employment experience

Gaining experience through real-world initiatives during an internship enhances your resume and helps you land a job.

Relevant Job Offers

In rare circumstances, the internship may result in a job offer.

So, How can you apply for an internship in Data Science and AI?

Your career in data science should start with a data science internship. It is crucial to choose an internship that will give you an opportunity to develop your technical abilities and obtain real-world experience.

To ensure you are internship-ready, you should take care of the following before applying for the internship:

Academic credentials, certifications, and references

About data science, Academic achievements, or certificates, improve your resume. Analyze the appropriate qualifications and pursue them as necessary. You can also obtain recommendations from professors and reputable data scientists to support your credentials.

It's time to start applying for internships now. An IBM-accredited data science certification course in Bangalore is the best way to showcase your credentials on your resume. 

The following are a few factors that will increase your chances of getting the data science internship of your choice.

Networking: The ability to network is crucial for landing your first internship. Start investigating your relationships by starting with known contacts, friends, and family, and finally, open networking by going to data science-related events.

• Send your résumé to all prospective contacts, act enthusiastically, and follow up regularly. Be quick to accept the first offer to talk about potential internships.

• Look through job websites like linkedin.com and submit your online application for suitable internships. Additionally, you can submit your application through the websites of your selected employers.

• Consider the internship options from the standpoint of learning opportunities and prospective future employment when you receive many offers.

Technically Ready

Strong conceptual comprehension and technical abilities are necessary for the internship role. You should excel in data preparation, machine learning modeling, and Python programming.

Data Science Projects

You should have completed 20 learning or capstone data science projects using fully operational machine learning algorithms. It is strongly advised that you keep track of your code developments in cloud repositories like Github so that you may show them to prospective employers to demonstrate your subject-matter expertise.

Conclusion

I hope this article will be helpful for obtaining a successful data science internship. Before wrapping up, I want to point out that while there is no foolproof method, the advice above will improve your chances of standing out from the crowd and pursuing your desired career. Never forget that persistence and patience are essential for professional success. Furthermore, if you want to start learning everything from scratch or want to upgrade your skills, I suggest you take up the best data science course in Bangalore. Learn and acquire hands-on practical experience to be confident before applying for any internship or job.

Good luck!