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This article would be a great help if you are about to select the Artificial Intelligence career path as a career option and want to know how to become an Artificial Intelligence Engineer?
If you are just curious to know about Artificial Intelligence as a career option, I assure you at the end of this article you will be able to find these two questions answered by your own.
- Is Artificial Intelligence career path a right fit for me or…not?
- Should I pursue this career path?
I divided this Artificial Intelligence career path guide into two parts.
In the first part, you will go through with the introduction part of Artificial Intelligence, where you would get to know; basic understanding of AI and why AI is the most discussable topic in the world and why everyone wants to know about it and why it’s creating so much buzz around the world.
The second Part is the technical part where you will learn what are the required skills, and tools I need to learn and the education qualification to get a job in the Artificial Intelligence.
Along with this, you will also get to know! About these things…
- Relation between AI and Machine Learning
- Best Online Courses to Learn AI
- Artificial Intelligence books
- AI Engineer Job responsibilities in an organisation
- Artificial Intelligence Sub-fields
- World’s top Artificial Intelligence Companies
- Future Career Scope
Also, we will know the step-by-step process of getting into Artificial Intelligence career path.
But before starting the topic, I want to inform you Artificial Intelligence is a vast field. And difficulty level is a bit high as compared to other career options existing in the industries.
I do not have the intention to intimidate and bleak you. I am just informing the right thing.
That does not mean you cannot do it and just let it go without giving a try. Everything is hard and impossible before trying.
Although, this is also true that the career growth in AI is more as compared to others career option. They earn well and also have lots of opportunities.
Anyone can achieve anything in their life with the right guidance and diligence to learn.
So without any further due let’s get started with the Part 1 of Artificial Intelligence career path
What is Artificial Intelligence (AI)?
The science and engineering of making intelligent machines, especially intelligent computer programs. – Professor John McCarthy
Prof. John McCarthy also is known to be as the father of Artificial Intelligence.
In other words, Artificial Intelligence is a way of making an electronics machine to think intelligently.
A robot or machine is said to be intelligent if they complete their task by itself and learn by their own mistakes, like a human child.
The motto of AI is to build a machine, who can think, learn, behave and understand independently as humans and even surpass him. And also able to adopt new situations based on current happening situations.
Difference between AI and Machine Learning
These two terms are correlated to each other and use interchangeably. For this reason, it creates lots of confusion in many of us brain.
But, they are not the same term. Let’s understand with an example to clear our wrong perception.
If AI is – tree then ML is – one of the main Branch of tree
As we know, Artificial Intelligence is ‘Smart’ then who makes it smart? Off course the ‘Data’ and who feeds that data to AI? Yes, you are absolutely right Machine Learning provide the data to AI.
Machine Learning is a subset of Artificial Intelligence. We can say that the backbone of AI is Machine Learning.
Without Machine Learning machine can’t able to perform any task on its own.
Therefore you have to get some knowledge of ML if you opt for Artificial Intelligence as a career option.
If you want to learn about Machine Learning and want to know various ML career paths, then do check our article: Machine Learning Career Path [Things You Should Know]
To become successful in the Artificial Intelligence career path you must have a clear understanding of how machine learns from scratch.
Without ML AI is completely zero i.e. without ML there is a point of AI
Types of Artificial Intelligence
Artificial Intelligence can be categories into three types based upon how intelligent they are and what are the things they are capable of doing.
Weak Artificial Intelligence
Weak AI also known as narrow AI. As the name suggests it is the weakest of all AI. Weak AI is the most common form of AI and can handle only some limited task. They are usually used for solving a single problem.
Strong Artificial Intelligence
Many scientist and engineer also named this AI as Artificial General Intelligence (AGI)
The aim behind this AI is to achieve critical thinking as a human brain did. And be able to do all the regular human task appropriately.
So far there is no AI who is called to be as Strong AI
Artificial Super Intelligence (ASI)
As for now, this is the final stage of Artificial Intelligence of AI, where AI will surpass the humans. It is not to be wrong if I say ASI could replace the humans.
That’s why researchers and many prominent people oppose the idea of developing Artificial Super Intelligence (ASI).
Success Examples of Artificial Intelligence
1. The most popular example of Artificial Intelligence is AlphaGo developed by Google DeepMind.
AlphaGo beat the professional Go player Lee Sedol in March 2016 in Seoul, South Korea. AlphaGo wins 4 round out of 5 rounds.
After this huge victory, Artificial Intelligence left a mark on the world and has changed millions of people views in a single night, who had been thinking it would be impossible to achieve.
2. One more success adds to the field of AI. When OpenAI defeated the world’s top professionals in the online multiplayer game Dota 2.
3. One more example we can talk about is Watson. Watson is developed by IBM’s DeepQA project team. It is also capable of giving answers to those questions, which is posed in natural language. Natural language such as speech or singing.
4. Sophia Robot: This humanoid robot developed by Hanson Robotics with the collaboration of Alphabet Inc (Google’s parent company ).
This robot was activated in 2015 and from that time she surprised many brilliant minds with her answers and expressions. Sophia can create more than 62 facial expressions.
Achievements of Sophia: First ever non-human holding the title of United Nations. Sophia is the first robot to receive citizenship from any country (In October 2017 Saudi Arabia gives him citizenship).
5. Atlas Robot: This humanoid robot developed by Boston Dynamics in the year 2013. Watch Atlas video on YouTube
Software Is Eating the World, but AI Is Going to Eat Software – Jensen Huang, Nvidia CEO
Applications of Artificial Intelligence
Artificial Intelligence has already touched our lives in many ways that you might not notice, for example…
- Suggested Ads pops up in your Facebook feed based upon your searching history or cookies.
- Have you ever played games such as solitaire, chess, poker etc. and you choose your opponent as a computer? You might not know but your opponent is an AI.
- Every time we go for google search some kind of AI being used to show us the best possible result.
- We need a translation between languages to understand different languages especially when we go to other countries. So we use Google translate, which is also using AI.
- Netflix’s movie suggestions based on movies you have watched in the past.
There are a plethora amount of AI examples available today I have listed only a few of them. Nowadays many mobile application and software is based on Artificial Intelligence. Actually, we are quite surrounded by Artificial Intelligence.
This would not be wrong to say Artificial Intelligence technology is growing at a fast pace and adapting all the different markets.
Knowing the above-mentioned examples and various applications, I am assuming you got the answer why Artificial Intelligence technology is creating buzz around the world and so why everybody wants to talk about it and know about it.
That is the reason why you are also here.
So, this is the end of Part 1 of the Artificial Intelligence career path and from now onward we will discuss Part 2.
Let’s understand, what are the things you should know? If you want to be part of this evolving and futuristic technology
Artificial Intelligence Career Path Prerequisites
1. Bachelor’s degree in any of the subject is required. But, Bachelor’s in computer science got more preference than others.
2. Mathematics: You should have known about these topics
- Graph Theory
- Statistics and Probability Theory
- Linear Algebra
3. Languages: If you know multiple languages such as Chinese, Spanish, English, Hindi etc. is a plus.
4. Science: Physics and Biology [In biology, you should go for Psychology and Neuroscience]
5. The knowledge of Mechanical, Electrical and Electronics is a plus.
Python is the most popular language in Artificial Intelligence technology. Therefore, Python is one of the most widely used programming languages. All credit goes to its simple syntax which is easy to learn and implement.
Skills required to become an AI Engineer
- Natural Language Processing (NLP)
- Machine Learning
- Deep Learning
- Algorithm design and development
- Knowledge representation and reasoning (KR)
- Programming Languages
- Neural Networks
- Graphic Design
- Pattern recognition (PR)
- Data Pre-processing
I am not saying to learn all these skills but If you possess multiple skills set then it would be easier for you to get into Artificial Intelligence and so the job. And so it’s easier for you to achieve your dream of becoming an Artificial Intelligence Engineer.
Tools/ Machine Learning Frameworks used in AI
These are the following tools or framework an AI professional used to develop an Artificial Intelligence machines.
- Apache MXNet
- Microsoft Cognitive Toolkit (CNTK)
- Spark MLlib
Among these frameworks, TensorFlow is the most popular machine learning library, which is developed by Google.
I think now you have realised that Artificial Intelligence is the vast domain therefore to get a job I will have to learn many different things?
That means, in order to learn all those skills will definitely take too much time. So my suggestion for all the aspirants of Artificial Intelligence is to learn a few skills and become an expert in those skills.
Or you can increase your learning speed by joining some online courses on the internet, which we will know next in this guide. With the help of those expert skills of yours, you can start your career in Artificial intelligence.
Best Online Courses to Learn Artificial Intelligence?
You can learn Artificial Intelligence from the comfort of your home and get a decent job in this amazing and futuristic technology.
There are many online learning platforms you can join to develop some of the required skills in artificial intelligence career path.
Searching on the internet for many hours for the best available online courses, I stumbled upon these following courses.
- Artificial Intelligence A-Z: Learn How To Build An AI
- AI For Everyone -by Andrew Ng
- Machine Learning offered by Stanford
- Deep Learning Specialization by deeplearning.ai
- Artificial Intelligence (Course Bundle) – Linkedin
- Machine Learning, Data Science and Deep Learning with Python
- AI & Deep Learning with TensorFlow
- MIT AI Course –Lecture Videos -Free
How to become an Artificial Intelligence Engineer [Step-by-Step] Guide
Many people want to learn Artificial Intelligence but they don’t. One of the biggest reason is they actually don’t know where to start learning this overwhelming technology.
So the confusion on How to get started actually stopping many people to make their first move on learning Artificial Intelligence.
But don’t worry this Step-by-Step guide help you to make your first move towards an Artificial Intelligence career path. And you will be known, what are the things I should start learning first.
[Step 1] Mathematics
Strong your mathematics and sharpen your mind by solving logical problems. This will help you to understand and create logics in the programmes, and eventually help you to learn programming language fast, which is the step 2.
In order to develop better applications and programmes you have to think more precisely and accurately (especially if you are writing codes for AI), which is only achieved if you are good at mathematics.
[Step 2] Programming Language
As I have already told, Python is one of the best programming languages for Machine Learning/AI. So why go for other programming languages. You can learn other languages though, it’s always good to learn new and more things but after the Python.
Here the key point is if you want to enter into this very domain you have to learn Python. However this not completely true.
So why I am saying that because Python has more machine learning libraries and developer community support as compared to other programming languages, most of the industries are working with Python.
Thus if you go for Python then you will make easier for yourself to get into Artificial Intelligence career path.
The choice is yours!
How to Learn?
 Follow up this website to learn the basics of Python https://www.learnpython.org
 Watch Python video tutorials on YouTube
 You can also join these two paid courses and learn from industries experts
- Programming for Everybody (Getting Started with Python), University of Michigan
- Learn Python Programming Masterclass
[Step 3] Algorithms
Algorithm plays a core part in machine learning, it tells a machine what to do next in a structured manner. These are the following machine algorithms you must know and understand how do machine learning algorithm works.
- Linear Regression
- Logistic Regression
- Support vector machine (SVM)
- Random Forest
- Decision Trees
- Gradient Descent
- Naive Bayes
- Dimensionality Reduction Algorithms
- K-Nearest Neighbors (KNN)
[Step 4] Data Preprocessing
Data Preprocessing is a technique of transforming raw data into an understandable data format. That is, you need to pre-process the data before providing data sets to the machine learning algorithm. And you must know that how to do that.
Read these two articles for more information about data pre-processing
[Step 5] Machine Learning Library
There are many machine learning library available for Python you can choose any of them. However, the most preferable libraries among AI Engineers are TensorFlow and scikit-learn.
Practice all the things you have learned so far in your chosen library.
[Step 6] Deep Learning
At this point, you have already gained knowledge of Python and Machine Learning and now it’s time to move on the next step of Artificial Intelligence career path which is Deep Learning.
Using TensorFlow start learning deep learning by solving some neural network problems.
You have learned all the required things which needed to become an AI Engineer. And now you need some real exposure which we will know in our next step.
[Step 7] Hone your skills
To hone your skills you can actually do many things such as…
- Attend AI conferences and Tech Talks
- The best way is to join the Artificial Intelligence Open Source community. For this, you can join GitHub community and participate on many ongoing projects. Here you will get hands-on experience on live projects. 100 Best GitHub Artificial Intelligence Projects. The more projects you do, the better you become.
- Join Kaggle. Kaggle is a platform to get AI and data science projects. You can also participate in a competition and could win the prize.
[Step 8] AI Engineer
Now it’s time for searching jobs in the Artificial Intelligence domain. So prepare your best resume and start applying for the jobs.
So these are the steps you will have to take if you want to get into the Artificial Intelligence career path and become an AI Engineer.
To get more and better opportunities in Artificial Intelligence career path, you have to keep yourself up to date with the very latest technology because new fields keep emerging as the time passes by.
Top 5 Best AI Books
Books are the great source of learning you will get comprehensive and in-depth knowledge of subjects. These are the few books I would like to recommend
- Artificial Intelligence: A Modern Approach
- Hands-On Machine Learning with Scikit-Learn and TensorFlow
- Programming Collective Intelligence
- Data Science from Scratch
- Deep Learning: MIT Press Book (Free)
What are the Sub-fields of AI?
Artificial Intelligence is a vast field, therefore it’s divided into many sub-fields. You can choose sub-field according to your preference and interest.
These are the following sub-fields comes under Artificial Intelligence.
- Neural Networks
- Machine Learning
- Evolutionary Computation
- Vision (Object recognition)
- Expert Systems
- Speech Processing
- Natural Language Processing
All engineers and scientists are said to be as AI Engineers/ Scientist, no matter in which sub-field they are working.
Each engineer has their own responsibilities, it could be different from others. They are all working together to develop and design a better Artificial Intelligence system.
Throughout your Artificial Intelligence career path you can be mastered in all of the AI Sub-fields but as a novice, you have to stick up to only one or two sub-fields.
What exactly does an AI engineer do?
I would suggest everyone before following an artificial intelligence career path or any other career path. You should have explicit knowledge of what types of work and responsibilities would come to your hand.
And this is the essential thing because it tells whether you are fit for that career option or not.
Also, it gives you positive inner vibes if you are knowing what exactly I am gonna do after spending so much time to learn all that required skills set.
Ok, so let’s understand what you are going to do as an Artificial Intelligence engineer.
- Perform research to advance the science and technology of intelligent machines.
- Implement and evaluate algorithms.
- Data mining and analysis of the data.
- Design, develop and maintain artificial intelligence-enabled managed services.
- Perform research to make AI/ machine learning more applicable to real-world problems.
- Architect, implement and test data processing pipelines.
- Provide software design and programming support to the team.
Top Artificial Intelligence Companies
AI Future Career Scope
The field of AI has been growing at a fast pace in the last few years. From Apple Siri to self-driving cars, AlphaGo, IBM Watson and many more innovations taking palaces.
Definitely, Artificial Intelligence is one of the trending careers in the world. And in the future, I don’t see any prospect of stopping that growth.
Companies all over the world are trying to implement Artificial Intelligence in their system to improve the efficiency of daily tasks and increase productivity.
In addition, you also need to be aware of the jobs prospect. Thousands of job openings in Artificial Intelligence posted on job Portals worldwide but at the same time, most of the positions are unfilled.
Because there are too few qualified applicants. If you decided to opt for a career in Artificial Intelligence. Then you must have good knowledge of AI.
After all, you are actually going for one of the most advanced technology.
According to Statista, Revenue of the AI market is expected to grow 170% in 2018 in comparison to 2017. Check this link to see the statistics Revenues from the artificial intelligence (AI) market worldwide from 2016 to 2025
That statistics shows lots of opportunities are coming for AI aspirants.
If we understand in general term, the consumption of using technologies is increasing day by day. We all love new and better technologies. That’s why we eagerly wait to buy new iPhone as soon as it launched in the market.
As of now, I don’t think so we can create a better and upgraded without using AI and Machine Learning.
So if you have decided to make a career in this hot trending technology, then you have taken a good decision. Lots! Of opportunities are waiting for you
I hope this article gives you a basic knowledge to pursue Artificial Intelligence career path. And I am sure you got your answer of How to become an Artificial Intelligence.
Let me know what you think about Artificial Intelligence career path. Share your opinions and experiences in the comments below!