AI Careers are one of the fastest growing career paths today.
Organizations like Intel, Uber, Wells Fargo, Samsung, Lenovo, IBM, Amazon, Facebook, Adobe and many more are hiring AI Engineers, not to forget that Google AI Jobs are also something which you could look at applying for in your AI Career. Many start-up companies are utilising AI Engineers to disrupt traditional industries in healthcare, transport and more.
So How To Start An AI Career ?
Well the first step to starting a career in Artificial Intelligence would be to learn the following technical skills.
- Design Patterns
- Statistics and Mathematics
- Machine Learning
- Deep Learning & Neural Networks
- Software Development Life Cycle
- OOPS, Classes
- Robotics, Instrumentation & Electronics (Optional)
- Programming languages like Java, C++, STL, Python, and Scala
How Do You Learn These Technical Skills ?
Start off be attending basic AI Career courses, programming courses including python, machine learning etc, AI workshops and learning as much as you can so you can know if AI is the correct field for you.
Here are some ways to get more knowledge on AI.
- Meet up with AI experts, participate in hackathons & conferences and register for relevant courses.
- Be an active participant by checking Open Source Libraries like Machine Learning Github.
- Practice on a few open source website to get familiarised with rectifications.
- There are many tutorials available on YouTube which you can watch.
- Make yourself a member with all the active AI community group.
What Should You Know Before Starting An AI Career ?
Remember Mathematics plays a crucial role in artificial intelligence. So, Calculus and Linear Algebra are the bare minimum to start your artificial intelligence journey. If you have done these subjects in school, which most students have, then you are on your way.
Interestingly Google AI Jobs require all or some of these qualifications :
- PhD in Computer Science, related technical field, or equivalent practical experience.
- Experience in Natural Language Understanding, Computer Vision, Machine Learning, Algorithmic Foundations of Optimization, Data Mining or Machine Intelligence.
- Experience contributing to research communities and/or efforts, including publishing papers at conferences.
- Programming experience in one or more of the following: C, C++, Python.
- Experience in project and people management.
- Experience in providing technical leadership for projects.
- Relevant work experience, including full time industry experience or as a researcher in a lab.
- Ability to design and execute on research agenda.
- Excellent publication record.
Should I Do A Udacity Nanodegree In AI Or A Phd Program ?
If you want to save on cost and time and dive straight into the cutting edge of artificial intelligence, I’d recommend courses such as the Udacity’s Deep Learning Nanodegree
But if you prefer a more traditional education then go get a Bachelor of Science degree which takes 3 to 4 years and then a MSc (Masters) followed by a PHD In Artificial Intelligence. Maybe you could start with a shorter course to teach you the basics, then if you like the material and find it interesting this would be a springboard into a more advanced qualification which would take a much longer time to complete.
In the meantime however you could get an AI Career started by completing a short course in Deep Learning here.
So What Type Of Jobs Can I Do If I Pursue A Career In AI ?
- Software analysts and developers.
- Computer scientists and computer engineers.
- Algorithm specialists.
- Research scientists and engineering consultants.
- Mechanical engineers and maintenance technicians.
- Manufacturing and electrical engineers.
- Surgical technicians working with robotic tools.
- Medical health professionals working with artificial limbs, prosthetics, hearing aids and vision restoration devices.
- Military and aviation electricians working with flight simulators, drones and armaments.
- Graphic art designers, digital musicians, entertainment producers, textile manufacturers and architects.
- Post-secondary professors at technical and trade schools, vocational centers and universities.
Take a Look at the Video Below Regarding AI Nanodegrees
Look At The AI Career Opportunities At Amazon
From Alexa to Amazon Go, we use machine and deep learning extensively across all areas of Amazon. With the mission to bring these innovative and valuable technologies to as many developers as possible, Amazon and AWS are investing in AI services.
We recently announced Amazon Lex, Amazon Polly, and Amazon Rekognition, providing cutting edge deep learning components for application developers without the need for deep mathematical skills, and AI engines for data scientists to create sophisticated, custom intelligent systems. Learn more about our current product offerings here.
We are looking for Software Engineers, Development Managers, Product Managers, and Scientists as we build tools across the AI stack. Applied Machine Learning experience is not required for all engineers, but our roles will provide a great way to grow in the field working with talented ML practitioners.
So What Industries Are Using AI ?
- Medicine: including interpretation of medical images, diagnosis, expert systems to aid GPs, monitoring, and control in intensive care units, the design of prosthetics, a design of drugs.
- Robotics: including vision, motor control, learning, planning, linguistic communication, cooperative behavior.
- Engineering: fault diagnosis, intelligent control systems, intelligent manufacturing systems, intelligent design aids, integrated systems for sales, design, production, maintenance, expert configuration tools (e.g. ensuring sales staff don’t sell a system that won’t work.
- Information Management: this includes the use of AI in data mining, web crawling, email filtering, etc. For example, a company in California uses AI to help retailers mine for consumer data by sifting through the ages, postcodes, and buying habits of people who buy goods over the internet. Google is a set of applied artificial intelligence platforms, which are able to ‘learn’.
- Space: control of space vehicles and autonomous robots too far from earth to be directly manipulated by humans on earth, because of transmission delays. Nasa uses AI to help plan and schedule space shuttle maintenance.
- Military Activities: this may be the area in which most funds have been spent. It is also not easy to learn about the details.
- Marketing: AI is being used to develop more targeted, relevant, and timely marketing programs to increase customer attrition rates.
Read Some Cutting Edge AI Career Articles Below To Get Your More Aquainted With An AI Career
Read these articles below on AI, Machine Learning and more from Industry leaders like Microsoft which will give you some insight and more ideas. Watch for more articles added daily.
Posted by Catherina Xu and Tulsee Doshi, Product Managers, Google Research While industry and academia continue to explore the benefits of using machine learning (ML) to make better products and tackle important problems, algorithms and the datasets on which
Posted by Yun Liu, Research Scientist and Po-Hsuan Cameron Chen, Research Engineer, Google Health Machine learning (ML) methods are not new in medicine — traditional techniques, such as decision trees and logistic regression, were commonly used to derive established
By Lance Eliot, the AI Trends Insider
Most people have a New Year’s resolution involving going on a diet or exercising more.
Apparently, here in Los Angeles, making a resolution to lead a frantic car chase and be relentlessly pursued by the
Posted by Andrew Helton, Editor, Google Research Communications This week, Vancouver hosts the 33rd annual Conference on Neural Information Processing Systems (NeurIPS 2019), the biggest machine learning conference of the year. The conference includes invited talks, demonstrations and presentations
By AI Trends Staff
We reached out to a range of AI practitioners for their predictions on AI Trends in 2020. Here is a selection of their responses:
Max Versace, PhD, CEO and co-founder, Neurala:
Max Versace, CEO and co-founder, Neurala
Customizable approaches to
Posted by Maithra Raghu and Chiyuan Zhang, Research Scientists, Google Research As deep neural networks are applied to an increasingly diverse set of domains, transfer learning has emerged as a highly popular technique in developing deep learning models. In