AlphaGo, Google DeepMind’s artificial intelligence (AI) program is the first-ever computer program to defeat a human Go player!
Built with machine learning techniques and systems integrated hand-crafted rules, AlphaGo’s legacy is spoken worldwide.
AI and machine learning have started taking the technology world by storm. In addition, job opportunities in machine learning are rising dramatically.
Major companies adopting machine learning and AI in business across industries reflect how job opportunities in the field will eventually propel.
So, it’s not surprising to see the number of AI and machine learning jobs skyrocket.
With job trends rising in both fields, it is certainly a good time for you to pursue a career in 2021.
Machine learning engineers are responsible for feeding data into models that have been defined by data scientists. Below are two possible scenarios:
Machine learning jobs are well-suited for tech professionals with great analytical skills. In-depth knowledge in the areas mentioned below is a must-have:
AI and machine learning are among the trending jobs in the labor market. And with multiple companies investing in these technologies, the demand for machine learning and AI engineers will surge.
Now that you’re aware of the skills you need to master, we will further discuss what you need to study within the next three months.
Month 1 – mathematics and algorithms
Month 2 – Machine Learning
Month 3 – Deep Learning
GitHub and Kaggle are two great platforms for you to get started with projects and building your own apps. Projects provide an overview regarding your hands-on experience in the technology. Since employers look for practical skills, having multiple projects on your portfolio is an added advantage.
A rigorous effort and hard work in these three months will equip you with practical knowledge in machine learning.
Perhaps you’re keen on knowing what the leaders in AI and machine learning have to say, well, attend a conference.
Below are a few lists of conferences you need to attend:
You’re not too late, you can still get an early bird ticket and register for the conference. Hurry while you still have the chance.
Perhaps this is the most challenging part of landing a career in machine learning because this is where it gets tough. Despite skills and knowledge, you need to tell the employers what they actually want to hear. Therefore, you need to be smart and wise to tackle the interview.
Here’s how you can ace it –
Though it is difficult, you can prepare and assess yourself and evaluate whether you’re a potential candidate. Here’s what you can start doing:
Engaging yourself with competitions on Advent of Code and Google Code Jam is an added advantage.
Also, having an array of machine learning projects to demonstrate to the employers can set you apart from the other candidates applying for the same job role.
The next step is to start looking out for relevant jobs. Don’t randomly apply for jobs, ensure you make a checklist of the areas you’re an expert in and start seeking jobs based on your skillset.
Your resume should demonstrate more of projects and practical applications and skillset rather than just theoretical achievements. Remember the employer is looking for candidates with hands-on experience in the technologies. Make sure you have what it takes for them to hire you. With AI and machine learning being the talk of the town, people have started building skills in the field.
Interviews might be challenging especially when it comes to getting a job as a machine learning engineer. You might be asked anything about the aspects of machine learning. Therefore, you need to start from the basics. They might ask you about algorithms, make sure you have solid points to back any answer you put out in front of your employers.
Give them a hint that you’re aware of deep knowledge in certain topics. Doing so gives them the leverage to choose you over other candidates.
Potential employers will most certainly give you a technical task to solve. These tasks are given just to check how capable you are in your tech skills. Therefore, you need to solve it patiently and don’t get anxious.
Below are a few tips to help you prepare for such tasks:
AI and machine learning are known as the technologies of tomorrow and will be critical for all businesses looking to stay relevant. Therefore, it would be ideal to say, that the highest-skill and the highest paying careers today fall under these technologies. As we move toward 2021 and beyond, there will be massive growth of opportunities across technologies like machine learning and AI.
The post A Complete Guide to Become a Machine Learning Engineer in 2021 appeared first on Brainstormingbox.