With the rise of AI-generated art and AI-powered chatbots like ChatGPT, it's clear that artificial intelligence has become a ubiquitous part of our daily lives. These cutting-edge technologies have captured the public imagination, fueling speculation about the future of AI and its impact on society. But amidst all the hype, it's worth asking ourselves: do we really understand the basics of artificial intelligence? While we may use AI chatbots and other AI-powered tools every day, many of us may not be familiar with the underlying principles and techniques that make these technologies possible. In this article, we'll explore some of the fundamental concepts in artificial intelligence, from supervised and unsupervised learning to bias and fairness in AI.

Chatbots are becoming increasingly popular as businesses seek to automate customer service and streamline interactions. Building a chatbot can be a fun and educational project to help you gain practical skills in NLP and programming. This beginner's guide will go over the steps to build a simple chatbot using NLP techniques. In this guide, one will learn about the basics of NLP and chatbots, including the fundamental concepts, techniques, and tools involved in building them. NLP is a subfield of AI that deals with the interaction between computers and humans using natural language.

There is a lack of enough qualified teachers across Africa which hampers efforts to provide adequate learning support such as educational question answering (EQA) to students. An AI system that can enable students to ask questions via text or voice and get instant answers will make high-quality education accessible. Despite advances in the field of AI, there exists no robust benchmark or challenge to enable building such an (EQA) AI within the African context. Ghana's National Science and Maths Quiz competition (NSMQ) is the perfect competition to evaluate the potential of such an AI due to its wide coverage of scientific fields, variety of question types, highly competitive nature, and live, real-world format. The NSMQ is a Jeopardy-style annual live quiz competition in which 3 teams of 2 students compete by answering questions across biology, chemistry, physics, and math in 5 rounds over 5 progressive stages until a winning team is crowned for that year. In this position paper, we propose the NSMQ AI Grand Challenge, an AI Grand Challenge for Education using Ghana's National Science and Maths Quiz competition (NSMQ) as a case study. Our proposed grand challenge is to "Build an AI to compete live in Ghana's National Science and Maths Quiz (NSMQ) competition and win - performing better than the best contestants in all rounds and stages of the competition." We describe the competition, and key technical challenges to address along with ideas from recent advances in machine learning that could be leveraged to solve this challenge. This position paper is a first step towards conquering such a challenge and importantly, making advances in AI for education in the African context towards democratizing high-quality education across Africa.

Artificial Neural Networks (ANNs) are extremely powerful. Recent developments brought scientists to create NNs with more connections than a human brain. To give you an idea, it is estimated that an average brain has 86 billion neurons and 100 billion synapses. On the other hand, the largest NN in 2022, "Megatron-Turing NGL 530B (MT-NGL)", a monolithic transformer language model, has 530 billion parameters. Still, the human brain is proficient in more than one field, MT-NGL is only specialized in language processing.

This course is aimed at offering the fundamental concepts of core Python programming language to the all levels of learners. This course is aimed at offering the fundamental concepts of core Python programming language to the all levels of learners. You will learn through videos, visual organizers and practice exercises. For a great hands-on learning experience, this course is packed with assignments, assessment tests, code challenges, quizzes, and exercises. Part-1: Core Python Programming Basics- starts with the basics of Python programming concepts like introduction, history & versions, features, uses, applications of python, data types, operators and control flow statements.

Data engineering is a critical part of data science. Most of the time, they occur together in business applications. However, there are some fundamental differences between them that you should be aware of when working with large amounts of data. In this article, we will help you get a better idea about what data engineering is – and how it differs from data science. Generally speaking, the bigger the data set size is – the more complex and technical task it becomes to analyze and process such an amount of information.

We are excited to share some of the best and most recent machine learning courses available on YouTube. There are many plans to keep improving this collection. For instance, I will be sharing notes and better organizing individual lectures in a way that provides a bit of guidance for those that are getting started with machine learning. If you are interested to contribute, feel free to open a PR with links to all individual lectures for each course. It will take a bit of time, but I have plans to do many things with these individual lectures.

I never read original papers of the greatest scientists, but I got so intrigued by the information theory that I gave Claude Shannon's seminal paper a read. In this single paper, Shannon introduced this new fundamental theory. He raised the right questions, which no one else even thought of asking. This would have been enough to make this contribution earthshaking. But amazingly enough, Shannon also provided most of the right answers with class and elegance. In comparison, it took decades for a dozen of top physicists to define the basics of quantum theory. Meanwhile, Shannon constructed something equivalent, all by himself, in a single paper. Shannon's theory has since transformed the world like no other ever had, from information technologies to telecommunications, from theoretical physics to economical globalization, from everyday life to philosophy. I don't think Shannon has had the credits he deserves.

There's literally no other course on Udemy that teaches Machine Learning without the need for programming knowledge or coding, using free open source software! Why Data Science and Machine Learning are the Hottest and Most In-Demand Technology Jobs. Data Scientist was recently dubbed "The Sexiest Job of the 21st Century" by Harvard Business Review, and for good reason! If you're looking for a fast and effective way to earn a 6-figure income without spending thousands of dollars in training, keep reading to learn about this revolutionary Udemy course. Glassdoor reports that Data Scientist was named the "Best Job in America for 2016," which was based on the huge amount of career opportunities and 6-figure average salary.

Ancient programming languages, such as C, Basic, or COBOL, followed a procedural style. The programs written in these languages consisted of a series of instructions, one after the other, that were executed step by step. To "enclose" functionality and be able to reuse it, they defined procedures (also called subroutines or functions). Still, global data was used, and it was tough to isolate specific data from each other. Thus, we could say that these types of languages focused more on logic than on data.