While normal education suffered a standstill in 2020, there were a lot of online courses and programs that were initiated by some of the most prestigious institutions as well as big tech giants so that the process of learning and skill development doesn't suffer. As the trend has been for a few years now, some of the most interesting initiatives were seen in the field of data science. In this article, we have listed some of the prominent data science education programs and initiatives in 2020. Microsoft, in collaboration with Netflix, has launched three new learning modules on beginners concepts in data science, along with machine learning and artificial intelligence. The design of these courses is inspired by the Netflix original film -- 'Over The Moon,' where a young girl Fei Fei, who builds a rocket to the moon, embarks on a mission to prove the existence of Moon Goddess.
TL;DR: The Machine Learning for Beginners Overview Bundle is on sale for £14.80 as of Dec. 20, saving you 96% on list price. Learning this technology is far from a walk in the park, but it's worth it. Ready to give it a shot? Check out this Machine Learning for Beginners Overview Bundle, a three-part pack of classes designed to walk beginners through the basics of machine learning without getting too in the weeds. The content spans seven hours total and requires no prior knowledge.
Deloitte has released a slew of predictions for 2021, including in the enterprise tech, data and tech, media, telecom spaces. Deloitte picked resilience as the theme for its 12th annual tech trends report; a word that became a mantra in nearly every organization after their 2020 plans were upended by the coronavirus pandemic. In a webinar Monday, the firm identified nine trends separated into three groups that focus on how organizations can use technology to digitize, modernize, and enhance their businesses. Some have been spurred by COVID-19 and some by changes that have been ongoing for years, said Scott Buchholz, a managing director with Deloitte Consulting and emerging tech research director. The first group is dubbed "Strategy, engineered," and addresses the notion that the corporate and tech strategies "have really become intertwined as we move forward and increasingly become one and the same," Buchholz said.
ADP is adding more artificial intelligence and machine learnings features to its DataCloud human capital management platform as it aims to compete with established HR software players. The updates add a series of tools to enhance workforce analytics. ADP, best known as a payroll service provider, has been expanding into HCM software. During a Dec. 2 investor conference, ADP CFO Kathleen Winters outlined the strategic importance of HCM software: We really serve all segments of the market, small business, mid-market, large enterprise space. The HCM industry is an attractive space.
The word artificial intelligence (AI) was coined in a proposal for a workshop called 2 months, 10-man study for AI on 31 August 1955. Coursera co-founder and computer science professor at Stanford University, Dr. Andrew Ng finds the COVID-19 fallout is producing a wobbly seismic shift in how the world trades, and he believes much of it will be everlasting. Market watchers like to follow trends because they are often a good indicator of what will happen next. The near future usually does look like the recent past, but not always. Sometimes we hit an inflection point and things veer sharply from the trend and that changes things in a way that can be truly transformational.
For the fourth edition of its "State of Service" report, Salesforce Research surveyed over 7,000 global customer service professionals to determine changing service standards in the midst of crisis, what new strategies, tactics, and technologies service organizations are turning to in the new normal, how service organizations are navigating abrupt changes in their work environment, and finally the impact and trajectory of field service during a time of social distancing. Here is the executive summary of the report's findings: Most every organization has been thrust into the future of work. What will determine failure or success in this brave new world? Every business is a digital business -- an important lesson in 2020. Seventy-seven percent of service agents say their company views them as customer advocates.
NASSCOM, at present, is offering several free online courses on artificial intelligence on its newly launched FutureSkills Prime Platform. The digital skilling platform was launched in association with the Ministry of Electronics and Information Technology (MeitY) to drive a national skilling ecosystem for digital technologies such as artificial intelligence, cybersecurity, cloud computing, data analytics, and the Internet of Things among others.
This course introduces principles, algorithms, and applications of machine learning from the point of view of modeling and prediction. It includes formulation of learning problems and concepts of representation, over-fitting, and generalization. These concepts are exercised in supervised learning and reinforcement learning, with applications to images and to temporal sequences. Learn how to perform supervised and reinforcement learning, with images and temporal sequences. This course includes lectures, lecture notes, exercises, labs, and homework problems.
We describe mechanisms for the allocation of a scarce resource among multiple users in a way that is efficient, fair, and strategy-proof, but when users do not know their resource requirements. The mechanism is repeated for multiple rounds and a user's requirements can change on each round. At the end of each round, users provide feedback about the allocation they received, enabling the mechanism to learn user preferences over time. Such situations are common in the shared usage of a compute cluster among many users in an organisation, where all teams may not precisely know the amount of resources needed to execute their jobs. By understating their requirements, users will receive less than they need and consequently not achieve their goals. By overstating them, they may siphon away precious resources that could be useful to others in the organisation. We formalise this task of online learning in fair division via notions of efficiency, fairness, and strategy-proofness applicable to this setting, and study this problem under three types of feedback: when the users' observations are deterministic, when they are stochastic and follow a parametric model, and when they are stochastic and nonparametric. We derive mechanisms inspired by the classical max-min fairness procedure that achieve these requisites, and quantify the extent to which they are achieved via asymptotic rates. We corroborate these insights with an experimental evaluation on synthetic problems and a web-serving task.