How to Build a Career in Artificial Intelligence as a Fresher
Despite the disruption caused by the pandemic, the hiring spree for tech professionals in the field of artificial intelligence (AI) and machine learning (ML) is hitting the roof.
Not only did COVID-19 highlighted the significance of AI across different sectors but also accelerated digital transformation.
Therefore, making AI engineers and AI specialists to be in excessive demand. Also, one of the major reasons why AI careers have started to lure every tech professional, even the newly minted graduates.
Let’s further delve deeper and try to understand the mindset of how things work with recruiters, especially when hiring a fresher.
Hunting strategies versus skills!
Which of these two options do you think grabs the attention of recruiters the moment they see your resume?
Not knowing what the employer expects from as a fresher is often a constant hindrance for job seekers in the tech field.
Well, tech companies don’t look for much from a fresher’s resume, though they expect you to be confident in the industry-specific skills. However, if you can demonstrate your expertise, you could be the ideal candidate for the company.
In theory, yes. Practically, no.
One reason why companies still struggle to find a relevant candidate to do the job.
If you want to command an AI career as a fresher, you’ll need to be exceptionally good in writing algorithms and use them to solve complex problems in real-time.
What freshers need to know before becoming an AI engineer?
Getting your first AI job can be dreadful if your coding ability is weak or if you don’t possess diverse AI skills. Most employers want candidates who’re experts in this domain. Candidates who not only have sound knowledge of AI and ML algorithms but also know which algorithms to apply when required.
How can you stand out?
Remember, hiring strategies might work at times but it does not guarantee you a job, especially not in the technical domain. Being a fresh candidate, you might need to consider certain factors before applying for a job.
Companies are hard-pressed to find relevant candidates for their firms.
- According to a report by the World Economic Forum, around 97 million new job roles might emerge by 2025.
- Jobs for machine learning and AI experts, and robotics engineers will be the most sought after. Some of which tech professionals are already looking to break into. AI is on the verge of creating multiple job opportunities in the labor market.
- A recent study says, individuals moving into the AI career lack key AI skills, but it is still possible to master these skills within a given timeframe.
Here are four crucial factors you need to know before you jumpstart your AI career.
1. Develop a solid foundation in mathematics, statistics, linear algebra, and calculus
Mathematics is not the most fun way to start a career in artificial intelligence especially if you don’t have the basic knowledge. Take your learning one step at a time. If you find the subject tough, start making your approach from a different angle. Try to focus on practical, build something yourself, and start implementing it through different analogies. Remember, if your math is strong, your foundation in machine learning and AI career will become strong.
AI and mathematics are said to be the two branches of the same tree.
If you want to thrive in the AI realm, you need to first get your foundation right.
2. Learn to code in Python, R, C++, and Java
Programming languages like R, Python, and Java are well-suited to solving complex AI problems. However, individuals need to know which language needs to be used based upon the nature of the problem. AI is already impacting the way we live and poses to be a significant part of every industry in the foreseeable future.
You can advance your skillsets by participating in coding or hackathons. This offers a great practical experience and it worth the effort. Kaggle, Halite.io, and CodinGame are great places to test your ability. Start developing projects by yourself, GitHub is one great platform where you meet other programmers, build individual projects, discuss problems, and gain additional knowledge from them too.
You can pick a project in some of the interesting topics such as reinforcement learning, computer vision, recurrent networks, one shot learning, neural network visualization and debugging, and NLP.
3. Become an expert in natural language processing (NLP)
NLP is one of the sub-fields of AI. This technology helps the computer understand, read, and process human languages. Being an AI engineer, you might have to extensively work with audio, text, or video. Another reason why you need to have sound knowledge in sentimental analysis, NLP, word2vec, and Natural Language Toolkit (NLTK) libraries.
4. Start advancing skills through AI certification programs
Over 120 million workers will require a retraining strategy in three years from now due to the AI impact on jobs, says an IBM survey.
AI is at the edge, freshers having an additional AI certification helps you stand out from the crowd.
Amid the present crisis, a certification can arguably increase your visibility amongst employers. Having said that, freshers will face cutthroat competition. Highlighting their work through projects will get them noticed by recruiters.
The AI-related role is the pathway to the jobs of the future.
Jobs won’t disappear but will be redefined: how ready are you?
What do you think? Will you be able to crack your first AI job as a fresher?