AI text generator ChatGPT, released to the public late last year, is so sophisticated that it has already demonstrated its ability to write coherent essays, generate sound legal documents and otherwise interact with humans in a convincingly conversational manner. One CEO even treats the tool from parent company OpenAI like a perennially available member of his executive team. "I ask ChatGPT to become aware of where my biases and blindspots might be, and the answers it gives are a really, really good starting point to check your thinking," Jeff Maggioncalda, CEO of online course provider Coursera, told CBS MoneyWatch. He said the tool helps him to be more thoughtful in his approach to business challenges, as well as look at topics from vantage points that differ from his own. For example, last week at the World Economic Forum meeting in Davos, Switzerland, Maggioncalda entered the following prompt: "What should I consider when giving a speech to prime ministers at Davos?" Another useful entry for business leaders would be: "What should I consider when I am restructuring my company?"
FREE COURSES: You can find a wide range of beginner-friendly AI and ChatGPT courses(Opens in a new window)(opens in a new tab) on Udemy. Some of the best of these online courses are available for free for a limited time. We'll admit that we find the recent acceleration in artificial intelligence development a little scary, but it doesn't seem to be going anywhere, so we're going to need to get over it. If you also feel somewhat intimidated by artificial intelligence and ChatGPT, you could consider an online course from Udemy. If you can't beat artificial intelligence, you might as well join it.
A Data Science course is a educational program that focuses on teaching students the skills and knowledge needed to work in the field of data science. This can include topics such as statistics, programming, machine learning, data visualization, and more. A Data Science course may be offered at the undergraduate or graduate level and can be a part of a degree program or a standalone course. The course duration can vary, it can be a few weeks long, few months or a full semester. Data Science courses aim to provide students with a comprehensive understanding of the field, including both the theoretical and practical aspects.
Are you looking for the Best Online Courses on Machine Learning?. But confused because of so many courses available online. Your search will end after reading this article. In this article, you will find the 20 Best Online Courses on Machine Learning. So, give your few minutes to this article and find out the Best Online Courses on Machine Learning for you. Machine Learning is very powerful and popular. Many people are shifting their careers into the ML field. The reason behind the popularity of Machine Learning is its power to make useless data into more meaningful data. Machine Learning models allow us to predict of various outcomes from the data.
Welcome to Machine Learning with Imbalanced Datasets. In this course, you will learn multiple techniques which you can use with imbalanced datasets to improve the performance of your machine learning models. If you are working with imbalanced datasets right now and want to improve the performance of your models, or you simply want to learn more about how to tackle data imbalance, this course will show you how. We'll take you step-by-step through engaging video tutorials and teach you everything you need to know about working with imbalanced datasets. Throughout this comprehensive course, we cover almost every available methodology to work with imbalanced datasets, discussing their logic, their implementation in Python, their advantages and shortcomings, and the considerations to have when using the technique.
The Covid-19 pandemic may not truly be over, but the boom it spawned in online learning and tutoring startups sure is. Now, with kids back in classrooms and venture capital funding for edtech down near pre-pandemic levels, entrepreneurs and venture capitalists have turned their attention to virtual reality, short form video and, first and foremost, artificial intelligence. "Investors are going gaga over artificial intelligence," says Tony Wan, head of platform at Reach Capital, a VC firm that invests in dozens of edtech companies. The education industry has been flirting with AI for half a dozen years, he notes, but suddenly, the relationship has turned serious. "Every business in ed tech--if it's not an AI business--needs to have an AI component," echoes Michael Moe, founder and CEO of GSV Holdings, a VC firm focused on the education and workforce skills sectors.
When Coursera CEO Jeff Maggioncalda first "started banging" on OpenAI's ChatGPT, he couldn't believe what he saw. "It looked like magic," he told Insider's Cadie Thompson at the 2023 World Economic Forum. The former English major turned ed-tech executive said that he was impressed by how the buzzy chatbot was able to "recombine word patterns" to "create new ideas." "The first time I sat down in front of ChatGPT, I said'this is not possible,'" Maggioncalda said. He called ChatGPT a "game changer" that is "blowing my mind" -- so much so that he now talks to ChatGPT daily and uses it as a "writing assistant" and a "blog partner." His interest in the AI extends beyond personal use.
This series of courses begins by introducing fundamental Google Cloud concepts to lay the foundation for how businesses use data, machine learning (ML), and artificial intelligence (AI) to transform their business models. The specialization is intended for anyone interested in how the use of AI and ML for the cloud, and especially for data, creates opportunities and requires change for businesses. No previous experience with ML, programming, or cloud technologies is required. The courses do not include any hands-on technical training.
The main goal of this specialization is to provide the knowledge and practical skills necessary to develop a strong foundation on core paradigms and algorithms of machine learning (ML), with a particular focus on applications of ML to various practical problems in Finance. The specialization aims at helping students to be able to solve practical ML-amenable problems that they may encounter in real life that include: (1) mapping the problem on a general landscape of available ML methods, (2) choosing particular ML approach(es) that would be most appropriate for resolving the problem, and (3) successfully implementing a solution, and assessing its performance. The specialization is designed for three categories of students: · Practitioners working at financial institutions such as banks, asset management firms or hedge funds · Individuals interested in applications of ML for personal day trading · Current full-time students pursuing a degree in Finance, Statistics, Computer Science, Mathematics, Physics, Engineering or other related disciplines who want to learn about practical applications of ML in Finance. The modules can also be taken individually to improve relevant skills in a particular area of applications of ML to finance.