Top Requirements To Get Machine Learning Internship

Machine learning is at the frontier of human development, and there is no better time to be involved in it than now. There are various opportunities for proficiency in this ever-growing new domain, from online AI ML Courses to being part of any computer science university course. But what specific skills must one have to land a machine learning internship? This article seeks to answer that question.

What Is Machine Learning?

Machine learning involves enabling artificial intelligence to learn from past data, always drawing upon its previous successes and failures, to grow and eventually make decisions without human intervention. It involves creating self-sustaining networks which run repeated iterations of an objective, with each iteration building upon the memory of the last one.

Machine learning has a range of uses in data sciences – from building a consistent interpretive model from regular data inputs to predicting later data entries. It can be used to aid in mathematical and/or statistical models which elicit conclusions beyond the postulations of human programming.

However, the uses of machine learning extend far beyond its source. Machine learning has many practical applications, ranging from adaptive traffic signals and self-driving vehicles to calculating progressive taxation.

A Career In Machine Learning

One may have a career that solely specializes in the study of machine learning, and/or focuses on adopting and improving the use of machine learning in a certain aspect of our lives. They may do freelance work or be employed under a company to fulfill the latter purpose. This need not necessarily mean that they will not carry out the former purpose – of studying and researching machine learning. Since this is a frontier endeavor, any action contributes to the pool of knowledge that any and all can draw from.

How To Land A Machine Learning Internship

A great first step into the world of machine learning is through an internship. This internship may be under a firm that solely focuses on machine learning, be it for research and/or application. However, one may also choose to do a flexible internship where they are expected to solve a problem – in which the candidate may choose to apply machine learning. In either case, one is expected to have a certain base of skills.

Here are those necessary requirements for a machine learning internship:

1. One must familiarize themselves with programming languages that highly contribute to deep learning. Python is a good place to start, given that it is the most commonly used medium of communication when dealing with machine learning. One may extend their knowledge of Python to apply it to resources like TensorFlow.
2. One must also know how to collect and store Big Data. It is useful to be familiar with storage databases, as well as resources that seek to process large streams of data and solve problems pertaining to it. Hence, one must be familiar with databases like MongoDB and Cassandra and also explore big data computations using Hadoop. Being familiar with other sources of storing data, like the more simple spreadsheet apps like Microsoft Excel and Google Sheets will also be highly useful.
3. A proficiency in decision-based mathematics, and/or algorithmic knowledge is of paramount importance. Since machine learning utilizes algorithms to form protocols that function without human control, it is far more necessary to have rigorous background algorithms. The possibility of errors and corrections is common and expected in machine learning, and a knowledge of mathematics helps the human in improving the machine in this endeavor. One must also seek proficiency in statistical mathematics to further aid how they deal with data.
4. While it is useful to understand and utilize commonly-used frameworks like TensorFlow and Hadoop, one may soon have to design their own software from scratch. A lot of companies benefit from unique interfaces that suit their workflow and objectives and simultaneously allow greater security from cyber-attacks. It is hence useful to have a knowledge of cybersecurity and have an adaptable understanding of software development. Using this, the candidate is far more marketable while they apply to a large range of internships.
5. Although this is not directly linked to technical knowledge, a lateral thinking mindset is probably of most importance. Any frontier technology involves solving new problems, and this is where a creative mindset is most useful. When it comes to machine learning, the human must learn from past iterations to better themselves just like the machine. Humans must find solutions to problems just like artificial intelligence undergoing deep learning, and hence the human must also have a willingness to adapt and find solutions.

Now that we have looked at the skills one must build on to land a machine learning internship, let us look and where one must search for such an opportunity.

This process can be undertaken by creating an online presence with a decent amount of searchability. One must have a profile on platforms like LinkedIn, to maximize their chances to get noticed. Here, one must attach their CV and give an accurate detail of their skillset in an articulate manner.

While the above helps the candidate to be found, they must do their own searching. Looking up websites that list internships, from Internshala to FreeLancer, helps one find opportunities they may have not known they wanted.

It is also useful to search for internships in the old-fashioned and probably most effective way – word-of-mouth. Talking to people involved in machine learning, or services that you feel will benefit highly from incorporating machine learning – will aid you immensely in finding and utilizing the correct opportunities for you. To go the extra mile, it is good to maintain contact with mentors and friends who have similar interests in this regard.

In Conclusion

Machine learning is a high-reward, high-demand, and high-profit endeavor to invest in. There are several ways one can utilize their talent in this aspect, and many opportunities to do so – provided a candidate is willing to learn and look.