Twenty million students started college this fall, and this much is certain: The vast majority of them will be taking on debt -- a lot of debt. What's less certain is whether their degrees will pay off. According to the survey Freelancing in America 2018, released Wednesday, freelancers put more value on skills training: 93 percent of freelancers with a four-year college degree say skills training was useful versus only 79 percent who say their college education was useful to the work they do now. In addition, 70 percent of full-time freelancers participated in skills training in the past six months compared to only 49 percent of full-time non-freelancers. The fifth annual survey, conducted by research firm Edelman Intelligence and co-commissioned by Upwork and Freelancers Union, polled 6,001 U.S. workers.

Rattle and R deliver a very sophisticated data mining environment. Data Mining with Rattle is a unique course that instructs with respect to both the concepts of data mining, as well as to the "hands-on" use of a popular, contemporary data mining software tool, "Data Miner," also known as the'Rattle' package in R software. Rattle is a popular GUI-based software tool which'fits on top of' R software. The course focuses on life-cycle issues, processes, and tasks related to supporting a'cradle-to-grave' data mining project. These include: data exploration and visualization; testing data for random variable family characteristics and distributional assumptions; transforming data by scale or by data type; performing cluster analyses; creating, analyzing and interpreting association rules; and creating and evaluating predictive models that may utilize: regression; generalized linear modeling (GLMs); decision trees; recursive partitioning; random forests; boosting; and/or support vector machine (SVM) paradigms. It is both a conceptual and a practical course as it teaches and instructs about data mining, and provides ample demonstrations of conducting data mining tasks using the Rattle R package.

IT is facing significant talent shortages, and new human resources AI talent recruiting systems are touted as being able to help. How do these systems work, and are they effective? The purpose of artificial intelligence hiring and talent scouting systems is to reduce the amount of work that HR or IT conducts in the activities of talent seeking, candidate evaluation and hiring. For example, if you're looking for a senior project manager, it's not uncommon to receive 300 or 400 resumes. All these candidates are applying because they believe they have the experience and the requisite skills to do the job you want to fill.

Companies are planning to increase their spending on artificial intelligence and machine learning as a result of the pandemic, and IT leaders believe that those initiatives should have been a higher priority for their organizations all along, according to a newly released survey by Algorithmia, a provider of ML operations and management platforms. Algorithmia's "2020 Enterprise AI/ML Trends" survey was completed in August by over 100 IT directors and above who are involved with those initiatives and work in companies with at least $1 billion in annual sales and 5,000 or more employees, the company said. There is little doubt the events of the past six-plus months have disrupted the plans of IT organizations. In fact, 42% of IT leaders responding to Algorithmia's survey said that at least half of all their AI/ML projects were impacted from a priority, staffing, or funding standpoint because of the COVID-19 pandemic. SEE: Microsoft's new feature uses AI to make video chat less weird (TechRepublic) But that doesn't mean those projects are going away--instead, their focus may have shifted, Algorithmia said. For example, 54% of IT leaders said their projects were focused on financial analysis and consumer insight prior to the pandemic.

IBM says within the next three years 120 million workers will need to learn new skills as a result of artificial intelligence (AI) in the workplace. The skills range from cybersecurity and data science to front-end and full-stack developers, according to IBM chief talent officer Diane Gherson. "These are the hotter skills out there in the market right now," she told FOX Business' Maria Bartiromo on Wednesday. "You're finding a shortage and every company is going to have to start developing these skills because they don't exist in enough numbers." And, according to Gherson, whether it's banking or industrial, every single company is "tuned into" AI of some kind. What's more, she said if you're not including AI in your business, you'll be left behind.

You could easily be fooled into thinking that slowly but surely, robots are taking over the world. Automated processes, machine-led factories, homes that are'smart', digital friends; just a brief glance at the things that some of our more sensational media outlets use to foster a fear in human's technological advances. But, they are exactly that. It is our advances, our creations and intelligence that have propelled technology to the dizzy heights that it reaches today. In an ever-changing job market, the UK has seen many traditional roles move to automated processes.

Data Mining with Rattle is a unique course that instructs with respect to both the concepts of data mining, as well as to the "hands-on" use of a popular, contemporary data mining software tool, "Data Miner," also known as the'Rattle' package in R software. Rattle is a popular GUI-based software tool which'fits on top of' R software. The course focuses on life-cycle issues, processes, and tasks related to supporting a'cradle-to-grave' data mining project. These include: data exploration and visualization; testing data for random variable family characteristics and distributional assumptions; transforming data by scale or by data type; performing cluster analyses; creating, analyzing and interpreting association rules; and creating and evaluating predictive models that may utilize: regression; generalized linear modeling (GLMs); decision trees; recursive partitioning; random forests; boosting; and/or support vector machine (SVM) paradigms. It is both a conceptual and a practical course as it teaches and instructs about data mining, and provides ample demonstrations of conducting data mining tasks using the Rattle R package. The course is ideal for undergraduate students seeking to master additional'in-demand' analytical job skills to offer a prospective employer.

To cope with the accelerating pace of technological changes, talents are urged to add and refresh their skills for staying in active and gainful employment. This raises a natural question: what are the right skills to learn? Indeed, it is a nontrivial task to measure the popularity of job skills due to the diversified criteria of jobs and the complicated connections within job skills. To that end, in this paper, we propose a data driven approach for modeling the popularity of job skills based on the analysis of large-scale recruitment data. Specifically, we first build a job skill network by exploring a large corpus of job postings. Then, we develop a novel Skill Popularity based Topic Model (SPTM) for modeling the generation of the skill network. In particular, SPTM can integrate different criteria of jobs (e.g., salary levels, company size) as well as the latent connections within skills, thus we can effectively rank the job skills based on their multi-faceted popularity. Extensive experiments on real-world recruitment data validate the effectiveness of SPTM for measuring the popularity of job skills, and also reveal some interesting rules, such as the popular job skills which lead to high-paid employment.

In 2017, people flocked to online classes about artificial intelligence, cryptocurrency, and data analytics. In 2018, expect more of the same, say leading online-education providers Codecademy, Coursera, edX, and Udacity. In response to a request from MIT Technology Review, they calculated their most popular courses of the past year and revealed which topics they think will lure the most students in the next. More than 29 million people have registered to take classes at Coursera, an online platform that hosts more than 2,000 courses from universities such as Stanford and Yale. Nikhil Sinha, the company's chief content officer, says many who enroll are "looking for a leg up in their careers" and gravitate to the platform's "cutting-edge tech" courses.

"People skills are more and more important in an era where we have powerful and pervasive technology," he says. "It sounds counterintuitive, but to beat the bot, you need to be more human." But a recent survey by the Wall Street Journal found that 89% of executives are having a difficult time finding people with these qualities. Some blame technology and the emphasis on STEM for the demise of things like communication, but Roehrig, coauthor of What To Do When Machines Do Everything: How to Get Ahead in a World of AI, Algorithms, Bots, and Big Data, believes those skills haven't diminished; they're simply needed in larger quantities now. "As machines do more routinized and lower-value-add work, more people are needed to work in context of what automation and AI cannot do," he says.