Hiring ads today have come a long way from Help wanted!. Companies looking for new employees need to focus not only on what they want from a new hire, but they also have to showcase the position they offer: present some history facts of the company, its goals for the coming years, fringe benefits, training plans, social responsibility actions, and so on. Because money is no longer the sole trigger for applying for a new job. People looking for a new job want to develop their careers, improve themselves, and generally get satisfaction and acknowledgement from the work they do. The company training plan is no longer regarded as an extra bonus but as a basic offer element.
Today's modern employees put great value on continuous learning opportunities at work. They are willing to put in all the effort to develop their careers, but they also have high expectations from any training course they attend. So what can L&D departments do about getting them engaged in the learning process and make the most out of each training session? Training and learning doesn't happen just in a classic training setting, at fixed schedules. It needs to be accessible anytime, anywhere.
AnyoneAI aims to democratize AI education by providing an intuitive and interactive platform to gain a solid understanding of AI and learn how to solve problems with it. The platform will provide lab-based tutorials where the learners will build their own AI models as they learn, and be able to see the "actual python code" of the model automatically generated as they build. The short "10 minutes" micro tutorials are specifically designed for learners to quickly learn and invest in themselves in small pockets of time spread throughout the day.
Lots of analyst misinterpret the term'boosting' used in data science. Let me provide an interesting explanation of this term. Boosting grants power to machine learning models to improve their accuracy of prediction. Boosting algorithms are one of the most widely used algorithm in data science competitions. The winners of our last hackathons agree that they try boosting algorithm to improve accuracy of their models.
AI, or Artificial Intelligence, is cropping up more and more in eLearning conversations--who's using it and how, and what it means for the future of corporate digital learning. As Learning Solutions prepares to explore AI from many angles, an overview of foundational aspects of AI might come in handy. Here, we'll introduce concepts and trends that are likely to appear in any deep discussion of using AI in eLearning. Artificial intelligence refers broadly to technologies that can learn and perform specific tasks. More complex tasks entail machine learning, a next-level technology that takes an AI machine or technology and teaches it to make "decisions" based on algorithms, learn from those decisions, and refine its own performance.