Internship in Data Science offers practical application of data science skills. Internship provides experience as a qualifier for your career. Internship as credential in your resume. Understand how to work in Industry by joining a University or Industry internship. With the growth of Industry by way of expansion in size and count of Machine Learning and AI product companies, access to Internships in Data Science are bound to grow. Internship in data science offers a win-win situation for both, Industry as well as students.
What is an internship in Data Science?
An internship in data science refers to the experience gained during a summer project, as part of an undergraduate research program, in the following types of data science related fields:
- Statistical machine learning and Big Data
- Data science and design
- Computer vision and pattern recognition
- Statistical modelling and modelling neural networks
- Computer science, statistics and machine learning
- Data visualization and visualization
Your internship can be for 3 months or more. Typical length of an internship would be around 2 to 4 months. Generally, students pursue this option if they want to further their education and also the chance to learn and understand their area of study.
Why should I intern?
If you want to understand how data science works. This is what’s being done by most people in data science. If you like creating stuff and solving problems in data then this is the finishing school. A lot of companies and courses do provide internships as part of their curriculum through Industry tie-ups. When you learn subjects like data science, ML/AI in a classroom you are not working on real life problems. It’s like studying medicine and till you don’t become a resident intern, you won’t get exposure. You data science internship bridges the gap between real environment and simulated classroom environment.
How do I apply?
You may use your regular university internship application portal or get registered on job portals. Additionally you can create your portfolio of academic projects on platform like GitHub. Many companies access these platforms to pick interns. Registering on niche internship platforms like Letsintern and Internshala are good options. I personally use these platforms to scout for interns in my technical data science team. Recommend to apply on opening for internship at Imurgence. These are virtual internships which can be undertaken from remote location.
What are the benefits?
Internship would give you hands on experience with a project at a renowned company. Apply the technical skills learned to a real-life project. Understand the solution process. Start building the networks. Gain knowledge to use these skills at future jobs. You will receive recognition in your resume.
Some requirements to apply:
- Student in computer science/Engineering
- Experience with R/Python
- Availability of 2 to 4 months to work on projects
Prerequisites for the internship
1-2 years of programming exposure is expected. Skills in Data Science, with background in statistical analysis and data modeling is required for a data science internship. A solid background in data visualization and reporting.
Internship as credentials
Our internship program gives you a unique learning opportunity. Our interns gain experience, knowledge and skills. Before joining our internship program, be sure to select a project that interests you and complete the appropriate steps to qualify. Your first step in internship is choosing a project that you are interested in. We have a wide range of projects available for interns to choose from. Choose the projects that interest you and let us know which projects you are interested in. Our internship program includes different types of tasks. In some cases, projects can include several steps. If you choose a project that includes multiple steps, select the appropriate project from the projects page. The experience letter from any internship would act as a credential to display in your resume. This would increase your chances on getting hired for a DS role. This would get rid of the problem of experience, which typically companies expect even from freshers.
Conclusion
It is important that you focus on majoring your soft skills, interview techniques, face-to-face presentation, group work, goal setting, problem solving skills and effective time management for proper career development. Let me know your views and comments on this.
