{"id":1534,"date":"2019-03-06T10:08:55","date_gmt":"2019-03-06T10:08:55","guid":{"rendered":"https:\/\/cloudxlab.com\/blog\/?p=1534"},"modified":"2019-04-16T11:02:50","modified_gmt":"2019-04-16T11:02:50","slug":"career-in-artificial-intelligence","status":"publish","type":"post","link":"https:\/\/cloudxlab.com\/blog\/career-in-artificial-intelligence\/","title":{"rendered":"Career In Artificial Intelligence: Myths vs. Realities"},"content":{"rendered":"\n

In recent years, career opportunities in artificial\nintelligence (AI) has grown exponentially to meet the rising demand of\ndigitally transformed industries. But while there are amply of jobs available\nin AI, there\u2019s a momentous shortage of top talent with the essential skills.\nBut why does this demand and supply gap exist? Many aspiring candidates wish to\njoin the AI bandwagon, but several myths hold them behind. <\/p>\n\n\n\n

Job site Indeed<\/strong>\nhighlights, the demand for AI skills has doubled over the last 3 years<\/a>,\nand the total number of job postings has upsurged by 119 percent. But,\njob-aspirants interest in a career in artificial intelligence seems to have\nleveled off. This clearly indicates employers are struggling to get good\ntalent. This is surely good news for all those planning to transit their\ncareers into AI! <\/p>\n\n\n\n

Well, building a career in artificial intelligence demands a self-controlled approach. You might be interested in a career switch because of the exciting opportunities floating in this booming industry or maybe for that long deep-rooted interest to pursue AI as a career. Regardless of what your inspiration is, the first step to moving ahead in the AI career path is to ditch the myths and misconceptions that for long has been blocking your path. <\/p>\n\n\n\n\n\n\n\n

Career In Artificial Intelligence: Myths vs. Realities<\/h3>\n\n\n\n

Myth #1: AI Is an\nExtremely New Field<\/strong><\/h4>\n\n\n\n

The term \u201cartificial intelligence\u201d was coined by John\nMcCarthy way back in the year 1956. Even though the concept of AI isn\u2019t new, it\nhas been creating more of a buzz across the globe in recent years. <\/p>\n\n\n\n

Myth #2: AI Can Be\nLearned Only In Prestigious Institutions <\/strong><\/h4>\n\n\n\n

This is probably one of the biggest myths, the reality is\nyou can learn as well as practice AI from the comfort of your home. Today there\nare many online learning platforms available for you to join and develop your\nskills in AI and enrich your resume – CloudXLab is one of them. <\/p>\n\n\n\n

Myth #3: Artificial\nIntelligence, Machine Learning or Deep Learning \u2013 All Are Same <\/strong><\/h4>\n\n\n\n

One of the most common confusions. AI is often misconstrued\nwith Machine Learning, Deep Learning, and even Cognitive Processing. But the\ntruth is that ML is a subset of AI wherein feeding data regularly train the\nsystems, and deep learning is a subset of ML. AI is the core and is broader\nthan ML, deep learning and cognitive processing. <\/p>\n\n\n\n

Myth #4: AI Is For\nTech Companies <\/strong><\/h4>\n\n\n\n

The initiation of AI is undoubtedly driven by technology\ncompanies. But now it is increasingly being incorporated by other industries\nand sectors. Right from healthcare sectors to financial, BFSI to e-commerce,\nFMGC and so on, every single vertical is keen to devour the AI-powered\nopportunities to yield significant benefits. <\/p>\n\n\n\n

Myth #5: Career In AI\nDemands Specialization <\/strong><\/h4>\n\n\n\n

You may read this everywhere, <\/p>\n\n\n\n

As an AI aspirant, you need to have skills and exposure in Statistics and probability, Applied Maths, Algorithms and coding, Programming languages like Python, C++, Java, R, and Distributed Computing<\/em><\/p><\/blockquote>\n\n\n\n

But That Is Just One Side\nOf The Story! <\/strong><\/p>\n\n\n\n

Beyond technical skills, AI demands an innate sense of\ncuriosity and a drive for problem-solving.<\/p>\n\n\n\n

Leaving technical background aside, an AI aspirant needs to\nbe analytical to understand data and craft algorithms and be incredibly creative\nto solve problems with new and innovative solutions. Simply put, learning AI\ndemands a combination of analytical ability, creativity, and problem-solving\nskills.<\/p>\n\n\n\n

You may want to look at our course AI for Managers. The idea\nof the course is that Managers should be able to predict the data given to\nthem. For them, it’s not obligatory to know the Math\u2019s behind it. In a similar\nway, AI for Managers course comes with only those areas that are highly focused\non solving and managing AI And Machine Learning Problems. <\/p>\n\n\n\n

Myth #6: Maths And\nProgramming Are Required For learning AI And Machine Learning<\/strong><\/h4>\n\n\n\n

Hear From Experts <\/p>\n\n\n\n

\nIs Maths & Programming Required for AI & ML | A Question of AI<\/a>