When Tesla CEO, Elon Musk, predicted that AI (Artificial Intelligence) would become smarter than humans by 2033, many thought it was just an exaggeration. But AI is on the verge of making history.
Yes, you heard it right!
The AI-driven chatbots, ChatGPT and BARD are already making their presence felt worldwide—it’s just the beginning. The AI revolution is here to stay and will transform our lives in ways we couldn’t even imagine.
For example, It’s not hidden how Siri and Alexa are now our best friends. They not just made our lives simple, but also guided us whenever we needed their assistance.
AI is expected to provide jobs to over 97 million people by 2025. The number is huge per se. But such jobs are not open to all candidates. Only skilled professionals who are well-versed in AI can apply for these jobs.
Many candidates feel learning AI is hard and not their cup of tea, but they fail to realize that learning AI from scratch is possible if you are dedicated and committed in your learning process.
Let us find out how you can learn artificial intelligence if you are completely new to this field.
How to Learn AI?
AI or Artificial Intelligence covers a variety of topics, including Machine Learning (ML), deep learning, and neural networks. You can learn it through online courses or boot camps.
Online courses offer a greater degree of flexibility and ease of access to necessary online resources, which include relevant and informative podcasts, guides, video tutorials, and webinars.
If you have a degree or diploma in computer science technology can look to do additional degrees in AI as further study options. AI is open to non-science and non-tech students, too; if you are equally committed and passionate about technological marvels.
In this information age, if you have a passion for AI, you can definitely learn it.
Now, we’ll take a look at how you can learn it without giving up your current job or course of study.
Can Anybody learn AI?
If you are from a non-tech background, things may be a bit difficult and challenging in the initial days. But once you get used to the core concepts of AI, you can easily pick up speed.
Freshers should try learning beginners courses for AI to get an idea about what they are going to learn in the subsequent stages.
The good news is you need not have coding knowledge to pursue a course on AI. However, knowledge of Python or R can be beneficial. Also, recalling the basic formulae of mathematics or going through those chapters again will give you an added benefit before you start the course.
Roadmap to Learn AI
AI is not here to complicate the lives of humans, rather it is here to simplify our lives, assisting us whenever we need advanced help or assistance. The idea is to work with AI and make it a friend—don’t feel threatened about it.
When the computer revolution was taking place, two and a half decades back, there was a massive hue and cry that it would lead to job losses.
But what we actually witnessed was the massive job generation for professionals possessing computer knowledge.
For example, if you take a look at SEMRush report, 86% of CEOs believe that AI is their mainstream technology. It also claimed that over 97 million new jobs will be created worldwide by 2025 for candidates possessing good knowledge of AI, machine learning, robotics, and big data.
So, there’s absolutely nothing to worry about AI, but possessing relevant knowledge and skills is essential.
On the job front, too, candidates possessing AI and relevant skills like Machine Learning, Big Data, and NLP (Natural Language Processing) tend to get more preference for relevant job designations than others who don’t know these concepts.
How Can You Learn AI from Scratch?
1. Get Back to Basics
If you want to learn AI from scratch, getting back to learning basic mathematical operations will be beneficial. Once you have gone through the necessary chapters of mathematics, you can go on to learn the essential concepts of Python.
2. Practical Operation
After you have got yourself familiar with the basics of mathematics and Python, you should start executing what you’ve learned on your PC. Before handling practical operations, you need to get yourself familiar with various data handling libraries, including matplotlib, NumPy, and others.
3. Data Interpretation
Data interpretation is the core of AI operations. Much of the time of AI professionals goes towards data processing and interpretation.
It’s the task of an AI specialist to extract valuable information and meaningful data from a pile of unstructured data. Without using the core principles of AI and big data, you can’t do data interpretation. So, you should learn how to properly and effectively conduct data interpretation tasks.
Where Can You Expect To Work?
If you are a tech professional and have good knowledge of AI and its operation, you can get highly lucrative jobs at Google, IBM, Apple, Microsoft, Open AI and other companies all across the globe.
After properly learning AI, you can expect to get a job for the post of ML Engineer, ML Assistant, Data Scientist or Data Engineer.
AI professionals are versatile and possess a high degree of flexibility. If you are good at your work you can easily handle multiple job responsibilities at ease. In turn, this will make you a natural choice for employers, and increase your chances of getting hired.
From sales, tech operations, finance, to marketing, AI professionals are required at all firms irrespective of their line of businesses and products/services they sell.
Is it not the right time to befriend AI and learn it rather than miss out on this golden chance, which could do wonders for your career? What do you think?