Machine learning has become a booming terminology that every multi-national company is leveraging these days. Right now, it is one of the fastest-growing fields in technology and has opened boundless job opportunities. There isn’t a more suitable time to get a machine learning job than this. Joining a machine learning internship is one of the best ways to start a career in AI, data science, or machine learning. In this article, we will discuss how to get a Machine Learning Internship.
Machine learning is about implementing the concepts of computer science and statistics upon data. This field teaches the system or computer how to learn or understand human actions through data. Machine learning algorithms help in prediction and decision-making. According to the CAGR report, the machine learning market will roughly grow from 1 billion USD in 2016 to 9 Billion USD by 2022. So, to become a full-fledged ML engineer, one should go through an internship in machine learning plus proper degrees and certifications. Let us now discuss the educational requirements an aspirant needs to get a machine learning internship.
Educational Qualification for getting a Machine Learning Internship
An aspirant who wants to jump into a ML career or get an internship should have a Bachelor’s or Master’s degree. Mostly a master’s degree in computer science, mathematics, or statistics is beneficial. Apart from that, the aspirant should also have sound knowledge of Linear Algebra, statistics, probability, and programming languages like Python and R. ML is not an entry-level career option. Therefore, the aspirants should also have a good knowledge and practical understanding of data science and software engineering. Furthermore, getting into a machine learning internship requires proper certification from reputed companies or institutes. There also exist degrees like M.Tech in Artificial Intelligence and Masters in Machine Learning and Deep Learning. These degrees will also allow the aspirant to get into the machine learning internship because of the specialization such a degree holds. Since ML discipline is software engineering-intensive, corporate professionals recommend obtaining a degree in computer programming or enrolling in a software engineering Bootcamp. Apart from basic educational qualifications, the aspirant should also have the following:
- A clear understanding of deep ML concepts
- A proper understanding of regression analysis and other statistical analyses
- Knowledge of data modeling & evaluation techniques – finding patterns in data and making predictions through algorithms
- System design and software engineering through programming languages like Java, C#, C++, Python, etc.
- Know how to apply ML libraries and frameworks to real-time situations
Machine Learning Projects and Work Experience
Since this domain is mostly about applying concepts, the aspirant must have software project development skills. Having some good software projects in hand, along with data science projects, will give you an upper edge to develop the portfolio well. These projects will showcase your software development skills and your proficiency in data science. However, if you opt for Masters in Machine learning or M.Tech in AI, the hiring team will definitely look for ML projects you have done during your masters. Working on real-time problem-solving projects during your graduation or post-graduation is always an added advantage from the rest of the candidates.
Let’s Build the Machine Learning Portfolio
Another essential weapon you will carry for getting a good ML internship at any reputed firm is your portfolio. Like other professional roles such as software engineering, web development, ML professionals also need a portfolio. This portfolio should showcase your projects, understanding of ML frameworks, and the datasets that interest you. The aspirant should look for Machine Learning Online Certification Courses or Bootcamps that will provide the aspirant with opportunities to work on real-world projects with actual startups.
Apart from all these, the aspirant can also join the Kaggle community, participate in ML hackathons, ML project competitions, or contribute to open-source projects. These practical works will enhance the weightage of your portfolio. It, thus, increases the chance of getting a good ML internship at a respectable firm.
Types of ML Projects to Add In Your Portfolio
There are four different categories of ML projects. These are:
- Work on the behavioral aspect of an ML project
- Work for characterizing the dataset or an ML project
- Implement an ML project on your comfortable programming language
- Work on an ML project that benefits a large group of people
- Work on implementing a property of an ML tool or framework
You should also upload these projects in GitHub or any other online project repository. Then you should include these project links in your portfolio as well.
Tailor your resume and search for Machine Learning Internship –
Resumes are not one-size-fits-all. The aspirant has to put effort into tailoring their resume highlighting their unique ML strengths and skills. There are various machine learning internship sub-roles. The aspirant should also have to tailor their resume according to the position they want to apply for the job. It is essential to design a resume that flatters the candidate’s background and credentials as per the job requirement. Let suppose you have done a simple Masters in Computer Science and not a Master in ML. But, you have a chock-full of passionate ML projects – then you should put the Project section above the experience section and just below the educational background section.
Another essential thing to keep in mind is to tailor your search for an ML internship through online platforms. The aspirants should create accounts in popular job searching platforms like LinkedIn, Naukri, Monster.com, Internshala, or in communities like Kaggle. It also increases the reach of getting a good machine learning internship. Lastly, having a good referral from any reputed ML engineer or professional also gives aspirants an upper hand in getting placed in a well-recognized firm as an intern.
To get a job as a ML intern or to practice machine learning does not require a license like that of a medical practitioner. If you are not a classically minted ML engineer, you should look for internship roles at startups. Aspirants with other ML internship experiences have clout.