Who can learn machine learning?
”Am I the right fit for a machine learning job?”
”I understand I need to deal with data, but do I really need to know machine learning?”
”Isn’t machine learning too sophisticated for an amateur?”
But how will machine learning skills help me?
”Yes, my colleagues keep discussing machine learning, but it seems too tough for me to give a try!”
Machine learning has confusing algorithms… Machine learning has advanced statistics… Machine learning has complex coding… Machine learning is a monster that can’t be tamed… Machine learning is a fad!
Have you ever asked these questions? Okay, maybe you didn’t ask them out loud but you did Google them!!
As a Data Science and AI academy, one of the most frequently asked questions to us is “Who can learn Machine Learning?”
We’re here to address just how hard it is to learn the subject and who can learn it.
Machine learning: The hype and the herd!
You must have heard educational platforms, blogs, posts and videos claiming machine learning is not that hard.
Everyone can learn it.
Everyone should learn it.
Well, it is your undeniable future!
Data science and AI are the uncrowned kings of futuristic jobs, but you also need to align your skills with the opportunities in this field to make machine learning a profitable investment for yourself!
You have to take stock of developments in the industry before you decide your place in it, or out of it! Your professional background isn’t all that relevant in determining whether you would flourish in the field of machine learning.
Understand this, separate yourself from the herd!
THE ANATOMY OF THE IDEAL ML STUDENT
Research skills
This is an obvious requirement when you’re exploring an industry, but all the more relevant in machine learning.
You need to be someone going above and beyond to understand trends, keep track of new developments and read about the application of the latest technology.
Community skills
Another important trait of a machine learning student is the ability to present himself to a community.
The machine learning and data science community is robust and communicative.
To constantly learn about new concepts, tools, developments and opportunities, you need to reach out and build your own space in the community.
In addition to that, your queries and problems are also fastidiously addressed by peers.
Go-getter
An ideal machine learning student is active and spirited. The field is not all about the theory and having that approach might not get you too far.
It is important for machine learning buffs to take initiative to learn and discover how to better themselves in the field.
Mugging up theory is not enough.
Not finding ways to apply your knowledge elsewhere will make your skills rusty in the end!
Analytical skills
Okay, we’re not talking about statistical analysis skills. Although if you do have them, it is an added advantage!
You should have an eye for detail, pattern identification and critical approach for dealing with machine learning problems.
Always keep your logical perspective intact when learning machine learning.
A technical bent of mind
Nope, we didn’t say technical skills.
You don’t need to be an ace coder but you should be comfortable with coding! Having a technical inclination is absolutely necessary to be able to handle to machine learning.
It works if you do not have a technical background or any previous knowledge of programming languages or tools.
Remember, if you plan on building a career in machine learning and cannot stand technical concepts and learning, this career is a major misfit for you.
Time Management skills
Another underappreciated quality is the ability to juggle time in the vast expanse of machine learning.
Time constraints exist for everyone, especially if you’re a working professional.
Staying on top of developments, finding the time to study and regular applications of machine learning concepts can be arduous.
You should be prepared to feel the walls closing in when the thought of lack of time strikes you. All you need is to set realistic goals and focus on your own, structured learning journey than getting overwhelmed by what’s on your plate.
What people think Machine Learning experts are!
There is no end to people’s imagination of the skills of a machine learning expert. Let’s burst a few bubbles and find out what machine learning experts are actually not!
No data wizards
Machine learning professionals aren’t data wizards. They don’t see datasets and get an epiphany on the best insights that can be extracted from them.
Yes, they do have initial hunches, intuitions and framework of approaching data but they’re also exploring for the most part.
There is no one size fits all scenario here.
You do get more experienced with practice and exposure but most of the data is unorganized and business needs are yet to be optimally identified which makes machine learning an experimental task.
No math magicians
Machine learning pros are not math prodigies!!
Yes, a fair amount of math does go into becoming a machine learning professional and a standard understanding of linear algebra, calculus and optimization is required when you try your hand at this subject.
No sophisticated statisticians
Machine learning does involve a lot of statistics.
You will need to brush up on some probability theorems to understand machine learning algorithms and concepts more clearly to build a successful career in machine learning.
No master coders
Machine learning requires a fair bit of coding knowledge but most people think that the patrons of machine learning are expert coders.
They are not!
Again a background in programming is most likely you to catapult through the learning process, but a lot of people across the world have successfully studied and practiced machine learning despite having no prior knowledge of any programming languages.
You know the most machine learning friendly language is Python.
Python is easy to learn and code.
It can be read as simple English, is open source and absolutely free for everyone. This makes Python a growing favorite in the market and a user friendly tool.
As a practice, researchers and academicians in the field develop most of the algorithms and models which are used by industry professionals to tackle their business problems.
As a working professional, you need to be updated and aware of the industry practices but the responsibilities of developing your own algorithms isn’t all that pressing.
You Need To Have Basic Data Management Skills
You must be thinking if nothing is imperative, why doesn’t everyone become a machine learning expert?
First things first, professionals come here from all fields but that doesn’t mean anyone would make a good machine learning engineer.
The entry barrier is high for most people, and those willing to go the distance walk back to the dugout after some math and stats is thrown their way.
So make sure you have the resolve to learn the subject before you invest your time and money.
As a beginner, you must know enough about data cleaning and structuring.
Integrating data, cleaning, treating missing values and exploring the data are fundamental steps in machine learning.
Make sure you have an advanced knowledge of data preparation before you deep dive into the space.
If you’re struggling whether machine learning is the right choice for you, take the test below and find out your best fit.
Machine Learning Aptitude Test
Ask yourself these questions!
- Do you have an understanding of the machine learning and industry trends?
- Do you build on this understanding by extensively reading the news, blogs, books, watching videos and listening to podcasts?
- Do you know how industries are using machine learning to their advantage?
- Do you understand how you fit in?
- Can your skills be polished and matched to a machine learning expert?
- Do you have an aptitude for learning and applying technical tools on a daily basis?
- Do you have the foresight to use mathematical and statistical concepts to extract maximum insights from data-sets?
- Do you have the appetite to constantly learn new concepts and techniques?
- The industry is fast evolving with newer breakthroughs made every hour. Are you ready to keep up?
- Can you place data driven techniques in a business context?
If you are convinced that your aptitude is a good match for a machine learning job, go for it.
It is undoubtedly the fastest-growing employment sector and has a lot to offer for newbies!
Although we do claim the rise of machine learning as fourth generation industrial revolution, machine learning applications are more or less in a fledgling state.
Big companies are deploying machine learning as quickly as they’re testing them.
While the number of patents for such companies rises, so does their quest for additional machine learning applications.
This entire ecosystem of trial-and-error and learning by doing has increased the risk appetite of leadership when it comes to hiring.
Also, there is a huge skill gap in the market.
Since the demand for such roles is shooting through the roof while the supply of fully trained machine learning experts is not even close, skills are lacking by a landslide.
This gap has created wondrous opportunities for amateurs everywhere.
If you’re wondering what level of expertise is required to crack machine learning jobs, the threshold is low enough!
All in all, in the starter phase, you don’t need to be well versed with everything.
There is a lot of learning along the way. All you have to do is be prepared to build on your skills and polish them as you progress.
The most important trait as a machine learning novice is to have a hearty appetite for learning. The web is filled with success stories of people with no technical background making their mark in the field.
There is no standard formula that works for everyone but hard work and perseverance has taken the center stage for every machine learning buff.
Now you know what goes into the making of an ideal machine learning student. If you feel that you can inculcate these qualities, learning the skills should not be such an uphill task.
Every line of work requires maintaining a constant thirst for knowledge and the right spirit.
Never despair with the amount of information available and the career choices of other machine learning professionals.
You’re on your own ride and as long as you’re in control, you’ll definitely reach your coveted destination!
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