Artificial Intelligence!! Does it mean robots?
Well, earlier it meant so; but now it is much more than robots or sci-fi movies of the 80s or 90s.
It’s present in your smartphone (without which you don’t stay even for an hour), your smart TV, and your virtual voice assistants such as Cortana, Siri, or Alexa. It’s there in your social media account, your favorite eCommerce sites, your Netflix (or any other OTT platform), your online grocer store, your banking or UPI payment app, etc.
So, artificial intelligence is:
- An intelligent unit developed by us
- It can perform and execute tasks skillfully and doesn’t require human instructions
- It can act and think rationally
Typically, intelligence illustrated by machines is called Artificial Intelligence. AI is an integral part of Computer Science that is meant to mimic human intelligence in machines. If you wish to learn Artificial Intelligence and make a career in this domain, Artificial Intelligence Course in Chennai is the best way you can go with.
Artificial Intelligence can be categorized into three different levels:
- Artificial Narrow Intelligence: This is also called narrow or weak AI as it is goal-oriented and is meant to perform low-level tasks. Virtual assistants are the most common example of weak intelligence.
- Artificial General Intelligence: This is also called strong or deep AI, where machines can mimic human behavior. Some of the most common examples of Artificial General Intelligence are facial and Speech recognition, hypotheses testing, analogy. This category of AI is under research and is yet to be exploited.
- Artificial Super Intelligence: a vague concept, Artificial Super Intelligence is expected to develop shortly. It is supposed to perform tasks more efficiently, develop and formulate its own set of emotions, etc.
Reasons for learning Artificial Intelligence
Today, AI is utilized in almost all automated tools that perform tasks that are otherwise tedious for us. The main reasons for learning this ever-evolving technology are:
- Great career opportunities:
The demand for professionals skilled and trained in Artificial Intelligence have been doubled in the past few years. It is expected that AI is going to replace 40% of blue-collar and white-collar jobs. In most of the established companies, around 15 to 20% of jobs are related to AI.
You can work as an AI Engineer, Business Intelligence Developer, Data Science Engineer, Machine Learning Engineer, Data Scientist, NLP Scientist, etc.
The median annual salary of an AI Developer ranges between USD 100,000 and USD 150,000 in the US while in India it ranges between INR 13,00,000 and INR 16,00,000.
Some of the big names looking for professionals who are skilled and trained in AI are:
- Google DeepMind
- Facebook AI Research
- Accenture, and more.
- AI assimilates huge amounts of data
Through our activities over the Internet, we generate massive amounts of data (around 2.5 quintillion bytes of data). Every swipe, tap, or click is the data we generate. And this data is going to grow consistently in the future. This has to be processed properly and we can’t imagine doing so through human activities. AI serves as a boon here as the task of processing these massive amounts of data is made easy through AI.
- AI provides improved user experience
AI helps applications to serve customers in a personalized, and eventually better way. You might have noticed the way YouTube shows the videos as per your preferences. If you listen to a pop song, it will provide you with popular pop songs. If you watch a video of a snack recipe, it will recommend you a list of similar snack recipes. So, it gives an excellent user experience.
There are numerous benefits of learning AI that cannot be stated in a single blog. If you wish to brush up on your skills in this technology, read below.
Steps to Learn Artificial Intelligence
- Fulfill the prerequisites
Some of the subjects that we study in our high school years are at the core of AI. they are:
- Fundamentals of computer science
- Probability and statistics
- Discrete mathematics
- Linear algebra
- Data structures
- R or Python programming
- Algorithms and their analysis
- Select a topic of your interest
If you select a topic you are really interested in, you will enjoy your learning process. Focus on the problem, try to find an effective solution to it rather than just fishing solutions on the Internet.
- Find a feasible solution
You may have found more than one solution to the problem. It’s time to find a feasible one. You require an algorithm to process data into a format that is understandable for machine learning. Now, you can train the model to give a result and check its performance.
- Improve the solution
The solution or model built in the previous step may be simple. It has to be creative so that it attracts users. Try your best to enhance all the components and check their performance again.
Share this solution with people and record the feedback. You may get important feedback regarding the performance of your model.
- Repeat the above steps for various problems
Practice can make you perfect. So, practice making solutions, rather effective and impressive solutions for different problems to gain expertise in building simple and complex AI models.
- Complete a Kaggle Competition
When you appear for this competition you are required to show up your skills, try various approaches to solve problems, and come up with the most effective solution.
This competition also enable you to collaborate with community members and also interact with people on the forum and share your solutions with others.
- Enroll Yourself in an online training course
The best way to learn Artificial Intelligence as a beginner is to take up an online training course. Some of the best courses allow you to learn at your own pace and train you through industry experts. Real-life examples make you gain expertise in the topics of your interest.
A course from Simplilearn covers the most important topics of Deep Learning, Machine Learning and the crucial programming languages required tpo build AI models.
Some of the popular topics covered in this course are NumPy, SciPy, Keras, Spark, Scala, Pandas, Python, R, TensorFlow, etc.
Enroll Yourslef Now!!