Data Science is a rapidly expanding field with many available opportunities. And it’s great if you’ve decided to plunge headfirst into this field! The first step is landing an internship in your dream company. Doing online projects and courses is a great option for learning Data Science but an internship is extremely important. It provides you with real industry experience and the chance to work with experienced professionals in Data Science. This can only help in your job search or who knows, you may even get an offer in the same company! So this article tells you all about how to land your first internship in Data Science.
Read on to find out the different technical skills you need in Data Science and also the various methods by which you can showcase these skills. You will learn a lot about the steps in getting an internship in Data Science that may even shape your future career in this very popular field!
What are the Technical Skills Required for a Data Science Internship?
Let’s check out some skills that are important for a Data Science internship. Don’t worry if you are not an expert in these fields as that will happen with time and experience. However, having some of these skills will only enhance your prospects for bagging an internship offer!
1. Statistical and Probability Skills
If you need an internship in Data Science, then Statistical and Probability Skills are a must. That means you should be familiar with at least the basics of Statistical Analysis including statistical tests, distributions, linear regression, probability theory, maximum likelihood estimators, etc. And that’s not enough! While it is important to understand which statistical techniques are a valid approach for a given data problem, it is even more important to understand which ones aren’t. Also, there are many analytical tools that are immensely helpful in Statistical Analysis such as SAS, Hadoop, Spark, Hive, Pig, etc. so it’s important that you have some knowledge about them.
2. Programming Skills
Programming Skills are also a necessary tool for getting an internship in Data Science. Python and R are the most commonly used languages for Data Science so you should be familiar with at least one of them. Python is used because of its capacity for statistical analysis and its easy readability. Python also has various packages for machine learning, data visualization, data analysis, etc. (like Scikitlearn) that make it suited for data science. R also makes it very easy to solve almost any problem in Data Science with the help of packages like e1071, rpart, etc.
You should also know basic Supervised and Unsupervised Machine Learning algorithms such as Linear Regression, Logistic Regression, K-means Clustering, Decision Tree, K Nearest Neighbor, etc. Most of the Machine Learning algorithms can be implemented using R or Python libraries so you don’t need to be an expert on them. However, it’s still good if you know how the algorithms work and which algorithm is required based on the type of data you have.
4. Data Management and Data Wrangling
You need to be proficient in Data Management which involves Data Extraction, Transformation, and Loading. This means that you have to extract the data from various sources, then transform it in the required format for analysis and finally load it into a data warehouse. To handle this data, there are various frameworks available like Hadoop, Spark, etc. Data Wrangling is also an important part of Data Science as it involves cleaning and unifying the data in a coherent manner before it can be analyzed to obtain any actionable insights.
5. Communication Skills
Yes yes, this is not a technical skill, but good Communication Skills can set you apart as a candidate for a Data Science internship! That’s because while you understand the data better than anyone else, you need to translate your data findings into quantified insights for a non-technical team to aide in the decision making. Another facet of this is data storytelling. If you can present your data in a storytelling format with concrete results and an interesting story then that will automatically elevate your value.
How to Showcase these Skills to Get a Data Science Internship?
1. Work on Projects
Projects are a great way to demonstrate your skills in Data Science. And it doesn’t hurt that they are fun to do as well! There is nothing more interesting than analyzing a data set to find the correlations between the data and obtain unique insights. There are many dataset sources where you can download and use data sets for free. These include Kaggle, Data.gov, Google Cloud Public Datasets, Global Health Observatory, etc. some of the popular projects that you can try on Kaggle if you are just a beginner include the Titanic Survival Project, the Personality Prediction Project, Loan Prediction Project, etc.
2. Create a GitHub Profile
It is also a huge plus point in your favor if you have a GitHub profile. Your profile is basically your data science resume that proves you can do what you say! Most hiring managers look at your GitHub profile as a part of the selection process so the more impressive it is, the higher your chances of selection. You should make sure to have clear problem statements, clean code files, and extensive personal projects on GitHub. If you are highly knowledgeable, you could even contribute to some open-source projects to showcase your skills.
3. Write Online Blogs
They say you have only understood something when you are adequately able to explain it to others. So consider blog writing an excellent learning tool where you can clarify your own concepts while also teaching something to others. You also get back thoughts and feedback from your readers which only helps you in improving yourself. There are many online platforms where you can write including GeeksforGeeks of course! You could also try out Medium or Quora.
4. Create Connections on LinkedIn
LinkedIn is a great way to build your professional network and gain more connections. Recruiters also check out your LinkedIn profile as it serves as a digital resume highlighting your skills, experiences, and education. You might even miss out on some internship opportunities if you don’t have a LinkedIn account or if it’s not regularly updated. And if you have a professional network on LinkedIn, you might even get some internship opportunities there!
How to Craft Your Resume and Prepare for the Interview?
Now you know what skills you need to land your dream internship in Data Science and also how to showcase those skills. But what about the most visible part of your application? The resume? And the actual make it or break it step which is the interview for the internship. How can you ace these steps? Let’s see!
1. Resume Writing Skills
Your resume is the first thing the recruiter or hiring manager will see so it’s very important that you make it impressive. This will increase your chances of getting an internship immensely. So make sure that there are no typing mistakes in your resume. Also, list all the relevant projects in Data Science and make sure you know them inside out. There is no use in mentioning a project that you can’t explain at the interview. And if you want to stand out, even more, you could create an infographic or data story of your resume using various data visualization tools such as Tableau.
2. Interview Preparation Tips
Now that you have reached the interview stage, you need to put your best foot forward to get your dream internship. The most important thing in the interview is to brush up on all the concepts of Data Science. You should also be intimately familiar with all the projects and experiences on your resume so you can talk in-depth about them. It is essential that you demonstrate the ability to think critically and analyze the questions in a structured manner. This is a more important skill than knowing any particular language or technology as those can be learned. Also, brush up on the company you are applying for so that you can understand the work culture and how your job description fits into that.
Now that you have understood all the technical and soft skills you need, it’s time to work on them. You can also showcase these skills on multiple platforms like GitHub, LinkedIn, etc. Then your next step is crafting an excellent resume and applying for various internships. You can do this on platforms like LinkedIn, Indeed, Analytics Jobs, etc. Then just prepare your best and ace the interview. Hope that you land your dream internship in Data Science and move on to a long and successful career!
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