Artificial intelligence is already reshaping society as we know it in both business and consumer realms. Early use cases with Alexa, autonomous vehicles and AI-driven supply chains, provide just a glimpse of the disruption that AI is poised to deliver in the near future and for years to come.
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Yet despite all the AI hype and initial successes, it remains in its infancy. That makes now the ideal time for young people to build the knowledge, skill sets and connections they need to capitalize on the fast-growing market for AI jobs and build a strong AI career.
One reason is simply practical. Gartner predicts that AI may eliminate 1.8 million jobs by 2020, yet is on track to create 2.3 million new positions. It clearly makes sense to map out an AI career path as new roles emerge that focus on problem-solving, collaboration and strategic decision-making.
The second reason is that AI offers a truly exciting opportunity to make an impact on our world. AI is an ideal career path for undergraduates and recent graduates with a passion for technology and an entrepreneurial spirit who relish a challenge and a front-line role in game-changing innovation.
AI has been called “the next Industrial Revolution,” and I think that analogy is spot on. The convergence of machine learning, big data and internet-scale cloud compute power is opening opportunities to transform healthcare, grow the economy, reduce waste, save energy, improve education, strengthen security and decrease poverty.
There’s virtually no area of society that will be untouched by AI. Given the myriad possibilities, how does a young person chart his or her course in the AI field?
Practical steps to an AI career.
One first step is to simply narrow down key interests and strengths. AI offers technological roles in data science, machine learning development and architecting an AI technology stack. And it offers plenty of positions as a user or analyst with AI software, or in sales and marketing, HR, customer support and more.
Company type is another important consideration, as B2B and B2C can be distinctly different work environments. Candidates should also target industries they gravitate to, be it technology, manufacturing, retail, higher education, services or others. To narrow down interests, hands-on research and learning is available through avenues such as:
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AI and data science courses. Many free and low-cost online learning opportunities in AI can be found at providers such as Udacity, Coursera, Codeacademy and fast.ai. These courses are a great way to build knowledge and enrich a resume.
Industry and company conferences. AI experts and thought leaders discuss trends at conferences hosted by NIPS, Re-Work, O’Reilly, Gartner and others, while AI vendors also sponsor conferences. Students and young professionals are often able to gain free or discounted admission.
Meetup.com. The website lists many regional in-person meetups among AI enthusiasts, as well as online groups and discussions on topical areas including machine learning, Python, R, data science and advanced statistics.
General immersion. Keeping up-to-date on fast-moving AI news and trends pays off. So does using AI products, sharing code on GitHub or entering a code contest on the global Kaggle community. In short, would-be AI professionals should learn as much as they can, as fast as they can.
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read more – copyright by www.entrepreneur.com
Artificial intelligence is already reshaping society as we know it in both business and consumer realms. Early use cases with Alexa, autonomous vehicles and AI-driven supply chains, provide just a glimpse of the disruption that AI is poised to deliver in the near future and for years to come.
copyright by www.entrepreneur.com
One reason is simply practical. Gartner predicts that AI may eliminate 1.8 million jobs by 2020, yet is on track to create 2.3 million new positions. It clearly makes sense to map out an AI career path as new roles emerge that focus on problem-solving, collaboration and strategic decision-making.
The second reason is that AI offers a truly exciting opportunity to make an impact on our world. AI is an ideal career path for undergraduates and recent graduates with a passion for technology and an entrepreneurial spirit who relish a challenge and a front-line role in game-changing innovation.
AI has been called “the next Industrial Revolution,” and I think that analogy is spot on. The convergence of machine learning, big data and internet-scale cloud compute power is opening opportunities to transform healthcare, grow the economy, reduce waste, save energy, improve education, strengthen security and decrease poverty.
There’s virtually no area of society that will be untouched by AI. Given the myriad possibilities, how does a young person chart his or her course in the AI field?
Practical steps to an AI career.
One first step is to simply narrow down key interests and strengths. AI offers technological roles in data science, machine learning development and architecting an AI technology stack. And it offers plenty of positions as a user or analyst with AI software, or in sales and marketing, HR, customer support and more.
Company type is another important consideration, as B2B and B2C can be distinctly different work environments. Candidates should also target industries they gravitate to, be it technology, manufacturing, retail, higher education, services or others. To narrow down interests, hands-on research and learning is available through avenues such as:
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR!
AI and data science courses. Many free and low-cost online learning opportunities in AI can be found at providers such as Udacity, Coursera, Codeacademy and fast.ai. These courses are a great way to build knowledge and enrich a resume.
Industry and company conferences. AI experts and thought leaders discuss trends at conferences hosted by NIPS, Re-Work, O’Reilly, Gartner and others, while AI vendors also sponsor conferences. Students and young professionals are often able to gain free or discounted admission.
Meetup.com. The website lists many regional in-person meetups among AI enthusiasts, as well as online groups and discussions on topical areas including machine learning, Python, R, data science and advanced statistics.
General immersion. Keeping up-to-date on fast-moving AI news and trends pays off. So does using AI products, sharing code on GitHub or entering a code contest on the global Kaggle community. In short, would-be AI professionals should learn as much as they can, as fast as they can.
[…]
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