From agricultural and industrial to the revolution of internet, we have now entered the era of Artificial intelligence. Almost every person who is fascinated by AI has seen a movie or read a story which revolves around AI. For eg. Terminator, Ex-Machina and etc. Inside the movies it seemed exciting but now it has entered our daily lives. Many interesting applications of AI are now being implemented on a commercial scale. But with the entry of more cool applications, there is a boom in the opportunities related to this exciting field. This article covers the artificial intelligence career path that discusses all the possible opportunities to serve this field. It also guides you through the complete path which makes learning fun as well as conceptual.
But why Artificial Intelligence?
The AI movies and robots like SOPHIA often excite people to know about machine learning. However, before starting a career in AI one must be clear about the facts why he/she is pursuing and will their interest be continued in this field for a big amount of time. For that, the knowledge of all the career paths and sub-fields of AI is very must. This article will give a diverse idea about the fields of Artificial Intelligence career path.
Artificial Intelligence is a field where an AI software is programmed to make decisions like a human. An AI works on two basic components data and algorithms. A brief detail is discussed at the end.
Interesting Fields in Artificial Intelligence to consider:
- Computer Vision: It is one of the most trending fields in artificial intelligence. As the name suggests it literally means seeing through the eyes of the computer. The idea is to program the software in a way that it can perceive things the way humans visual cortex does. Cool real life applications like detecting the unhealthy leaves of a plant, and correct yoga pose detection are already implemented. Many more are yet to come.
- Audio AI: As computer vision works on images, audio AI involves sound processing, digital signal processing to find patterns in sound so that AI can make decisions on the basis of patterns. AI can also produce music in the way you want, i.e genre tempo, etc. Chatbots are widely used nowadays and required in almost every other industry. Building chatbots is a very wide career option discussed below in detail.
- Robotics In AI:Robotics combined with AI is one of the biggest wonders of humanity. Here robots are programmed to make intelligent decisions and implement them. For eg. Robots used in security purposes are doing exceptionally well.
- Natural Language processing: NLP revolves around interaction of computers with human languages. Can machines understand the meaning of sentences? Can they feel the emotions in a sentence? Well NLP has made this possible. Poetry generation, script building along with sentiments in a sentence are widely used applications.
These 4 are mostly applied sub-fields of AI. These fields in many permutations and combinations are mixed to form a career option in the fields of AI. Artificial intelligence career path is a combination of all these sub-fields to solve real life problems.
- Healthcare AI: This has surprised the world by giving results even better than doctors in certain diseases. Recently an AI powered device was detecting skin cancer and heart attack possibility better than top doctors in the world. Disease detection is mostly done by using algorithms to find patterns in medical reports/images. Based on those patterns,predictions are done on new reports.
- Agriculture AI: This is expected to be the most promising field in future. From detecting seed quality using computer vision, to quality of manure further applying robotics for harvesting and removing infected leaves, many wonderful projects are possible.
- Business and stock analysis using AI: If you have an interest in stock markets along with building algorithms then this is a perfect path for you.
Stock price prediction using machine learning and AI has given fruitful results surprising big companies in the WALL STREET. There are so many new opportunities by big companies like Goldman Sachs as they are hiring ai experts to build stock price predictors.
- Chatbots are a must for every business nowadays. Every type of industry are using chatbots as their representatives to customers. Chat bots are more fascinating, less manipulative and answer more clearly than humans. Chatbots are customized by each company related to the specialization and area of work. Building chatbots is going to be a big career option in future. The best part is, one does not need to be a hardcore programmer to build a chatbot. Simple tools are available by which you can build very smart chatbots with very little or no programming.
- Self Driving cars: Have you ever heard of a car without a driver. 50 years from now (2019) it was almost considered impossible to build self driving cars. But now with the evolution of Artificial intelligence self driving cars are being tested on roads. Tesla, Google have already made this technology possible. They also provide working opportunities to interested ones in this field. Since this is a very big field apart from programming a lot of options are there in the world of self driving cars.
- Research : Life on other planets-> NASA has already built so many robots and machines that are searching for extraterrestrial life form on Mars. NASA has also created opportunities for those who want to join their research program to search for life on other planets. Not only other planets but also in the remote areas where humans cannot go this research is being carried out. This is an interesting artificial intelligence career path to choose.
- Game development: With AI spreading in all the fields AI games is a new area to explore if you are interested in gaming. AI is largely used nowadays to predict the opponents behavior in the game. Apart from this researchers are linking AI with video games to give 3D gaming experiences. This is a fun and entertaining field to go for.
- Art and Painting using AI: Nowadays software are able to recognize color patterns and sketching,stroking styles and replicate that in a mixed way. Neural style transfer which means to apply the style of one image to another proves to be another wonder of AI.
- Music generation and AI: Musicians have something new to add to their daily lives. AI has also started producing music on its own. You just decide the tempo, rhythmic style, genre along with the emotion and it will generate the music for you. Google AI Magenta is the perfect example.
- AI in law enforcement: With the number of crime rates increasing day by day, the San Francisco Police gathered all the data about the type of crime, location, timing, day along with the past case jurisdictions. AI was again giving amazing results by predicting the possibility of crime in a particular location at a particular date and time. Data collection is the most important part in this problem. Further pattern recognition is the next most important thing. Many similar problems can be solved by AI.
How to get into artificial intelligence:
There are two sub-fields in Artificial Intelligence: Data Science and Machine learning. To be very honest they are quite relatable to each other. Data Science is the analysis of data where we work on big data.
Data Science and Machine learning career path:
- It involves collection of data maybe through surveys, previous records, cameras, sensors or anything.
- Data processing: Process the data in the form you want to use it. For example if we are working on facial recognition, segment out the face from the image. Remove any background noise that is not useful for our problem solving.
- Finding patterns in data. Recognizing the patterns and feeding them into algorithms through the process of machine learning.
- Training the algorithms to make predictions on the basis of the program.
Starting as a data scientist requires knowledge of a programming language like Python, R, octave or Scala and further a deep knowledge of machine learning.
Deep learning is just a sub-field of machine learning. It is widely used nowadays like in computer vision explained above, self driving cars, etc. You can learn deep learning from here.
It involves analysis, processing and cleaning of data to find out useful information from it. Once data is gathered you have to process it in the way you want. Best way to start a career in data analysis is starting with a course. Building networks through websites like LinkedIn and git-hub is also important as in many countries this career option is yet to flourish.
Data Mining: It revolves around analyzing big data, finding patterns and making new patterns from existing patterns in the data. Data mining is an intersection of data science and machine learning. This is one of the best courses to start with data mining.
The correct and efficient way to begin:
There are so many courses available on the internet to start with data science/mining or say machine and deep learning. Due to a lot of variety there exists a confusion among beginners which one is the best. Even if you purchase the best course, there is a lot of possibility of losing interest in between the course.
Hence to maintain the motivation and enthusiasm to pursue any of the options above the best way is to start with a small project. Projects contain variety of learning and one can understand the flow how things are built.
But even to start a project some knowledge of python or any language and programming skills are required.
Many simple projects on computer vision, NLP, stock price prediction are there on this site in the sub-fields that you can start with according to your interest.
After that if you want to inquire in a specific field you can go for courses as this time things start making sense. Doing things without knowing where they are applied makes it quite boring to learn.
- On coursera there many amazing courses for Deep Learning and Data Science.
- Fast-AI is an amazing platform to the ones who have a decent understanding for machine learning.
- OpenCv and Pyimages are also interesting websites that teach you how to start with basis projects.
- The Stanford course for Neural Networks can be found on Youtube.
- By searching for simple projects on google related to your field, you can find an immense amount of projects with their implementation and understandings.
Read an interesting insight on preparing for the future of artificial intelligence:
Entering the industry and freelancing: Once you are comfortable with a decent level of projects and want to go for commercial projects then to approach people related to your fields you have to build networks on:
And many more. By entering groups like computer vision for pattern recognition on LinkedIn, one can know what is really happening in the world of AI. Simple google search does not tell much about the real life projects on AI. A lot of free lance work is provided on the basis of projects you have done and your performance. Building networks is the most important part as AI is a field where you cannot get a job directly by learning something and applying it conventionally. You have to be creative and only through your projects, clients give you work.
Also know about how the future of AI will shape reality of life and hence the possible job opportunities below.