Artificial Intelligence plays a crucial role in our lives with a myriad of functions, ranging from helping in our homes in the form of voice assistants Alexa, Siri or Cortana, to solving complex algorithms and improving cybersecurity. Artificial Intelligence has also gained traction lately because of the various inventions and innovations in the tech world and has been widely adopted by multiple industries and organizations. This unprecedented growth calls for trained professionals in the field of Machine Learning and Artificial Intelligence to cater to the growing needs of the organizations. Artificial Intelligence and Machine Learning jobs have a growth rate estimated to be approximately 344% according to statistical data of 2019. They offer a variety of jobs due to their wide application in supply chains, e-commerce, Human Resource Management, Healthcare, Sports, Aviation, Agriculture, Algorithms, and many more.
What is Artificial Intelligence and Machine Learning?
Artificial Intelligence is software that learns in ways similar to humans. It mimics humans and is advantageous to the industries since it is far more efficient in solving complex problems. Artificial Intelligence is also extremely fast and helps humans make intelligent machines and takes over some of the jobs to reduce cost and time, and increases efficiency. Machine Learning is a subset of Artificial Intelligence, and it is the process through which AI learns concepts.
Machine Learning consists of various algorithms that train Artificial Intelligence. One can say that they ameliorate human capabilities. AI and Machine Learning have tremendous scope in the present scenario and in the future as they play a vital role in our lives. A normal consumer uses AI in booking cab rides, streaming movies, and as home assistants. Businesses use AI to reduce costs and time and assess risks.
Machine Learning can be broadly divided into two categories:
- Supervised Machine Learning- In this type of machine learning, data that has been recorded in the past is fed to the AI to program it to analyze the present data and perform a variety of functions such as risk analysis. The machine is taught to identify different types of data, make predictions, and even sort the data.
- Unsupervised Machine Learning – In this type of machine learning, the data which is fed into the system is unclassified and unlabelled. The system learns by exploring the available data and analyzes patterns to draw inferences without any previous information.
Every industry is looking into expansion and the knowledge of Artificial Intelligence and Machine Learning is bound to bring forth bright career opportunities for motivated individuals. They can start their career and seek better pay and opportunities. The salary of machine learning engineer salary far outpaced other technology jobs in the market. The average salary for a Machine Learning Engineer in India is ₹686281. As ML being adopted by almost all companies to increase ROI and improve customer experience, there is a brilliant career opportunity ahead. With the demand skyrocketing, and if combined with the importance of Machine Learning, a person can safely start their career in the field and earn good money.
Subsets of Machine Learning
Apart from the two broadly classified methods of machine learning, there are also three subsets to work with. Each subset offers an opportunity of specialization for people who are keen on pursuing a career in AI.
- Neural Networks- Neural networks help the machines in classifying the information and even recognizing images. Machines will also be able to accurately predict and suggest viable decisions by analyzing data input.
- Natural Language Processing (NLP) – NLP provides the machine with the skill to identify a human language. This, in turn, will allow the machines to respond to humans.
- Deep Learning – Deep Learning allows machines to process data through neural networks and it can be applied to various other parts such as speech to come closer to human thinking and decision making.
- Machine Learning Engineer – The engineer has to run different experiments with the help of various programming languages such as C++, Python, and Java. They will also be responsible for implementing appropriate ML algorithms and running machine learning tests and experiments.
- Data Scientist – A Data Scientist’s job is to collect and analyze vast amounts of data and provide actionable information. This information is used by companies. The data scientist uses machines to analyze the data and has to be proficient in Machine Learning and programming languages such as Python and SQL.
- NLP Scientist- A NLP Scientist provides the machine with the ability to communicate. The machine has to learn speech patterns and even translation from different languages to communicate with humans. Math is the backbone of the NLP role.
- Business Intelligence Developer – A BI developer has to be proficient in business analytics and machine learning to analyze vast amounts of data and provide company executives with insights. This data is required to carry out efficient business decisions.
- Human-Centered Machine Learning Designer – The job requires to work with product, engineering to find out the right experience and make great user-centered choices. An example is Netflix. The designer has to program the machine to learn and analyze such patterns.
Machine Learning and AI are deeply woven in our everyday lives and their functions range from e-commerce to home assistants and much more. With the advancement in technology and companies looking to shift to AI, lucrative job opportunities have been created. Pursuing Machine Learning training and AI is a sure-fire way to start your career and inevitably progress in it. Good luck!