How to learn JavaScript using ChatGPT

May 27, 2023 Coin Telegraph

Discover how to learn JavaScript effectively using ChatGPT, an AI-powered language model.

Imagine yourself as a future programmer eager to learn JavaScript, one of the most popular languages for web development. If you are looking for an interactive and collaborative way to enhance your understanding of JavaScript concepts and improve your coding skills, ChatGPT, a language model, may help you in this endeavor.

One can converse with ChatGPT as their virtual learning partner, asking questions and looking for explanations about essential JavaScript concepts, such as variables, data types, operators and control flow diagrams. This article will explain how to learn JavaScript using ChatGPT.

Start with the basics

One can ask ChatGPT questions on the basics of JavaScript. Users can inquire about variables, data types, operators and control flow structures, such as loops and conditionals. Users can effectively understand these topics by looking for clarifications and illustrations.

Request code snippets

One can ask ChatGPT for code snippets or examples if they’re attempting to figure out how to implement a certain feature or resolve a problem with JavaScript. This enables people to research and evaluate the offered code to understand how it functions.

Seek explanations for error messages

Ask ChatGPT for help if you’re having trouble understanding error messages or other problems with JavaScript code. Users can ask for assistance in comprehending the issue and locating viable solutions by explaining the error message or offering pertinent code samples.

Explore JavaScript libraries and frameworks

There is a sizable ecosystem of libraries and frameworks for JavaScript. Users can query ChatGPT about specific libraries or frameworks they are interested in, and it will provide information, best practices and illustrative code. Users can use this to better understand how to use outside tools in JavaScript applications.

Learn JavaScript concepts and patterns

Users can gain a deeper understanding of JavaScript as a programming language and learn about industry best practices by having discussions with ChatGPT on JavaScript design patterns, architectural ideas or advanced techniques.

Share and review code

Users can send ChatGPT their JavaScript code for evaluation and comment. They might ask for general code improvement advice or specify the exact issue they are seeking to tackle. ChatGPT can offer advice, point out areas for improvement and suggest different strategies.

Collaborate with ChatGPT on projects

If users are working on a JavaScript project, they can discuss their project with ChatGPT. They can explain the requirements, ask for guidance on project structure or seek suggestions for specific features. ChatGPT can act as a collaborative partner, offering insights and helping users brainstorm solutions.

Related: How to learn Python with ChatGPT

Explore additional resources

Although ChatGPT can be a great help, users should also use other resources to round out their education. Users can practice coding and solidify their knowledge by using online lessons, documentation, coding challenges and interactive platforms.

5 Free artificial intelligence courses and certifications

May 1, 2023 Coin Telegraph

AI certifications

Discover five free AI courses and certifications to help you expand your knowledge of artificial intelligence and machine learning.

Learning artificial intelligence (AI) is becoming increasingly important for both technical and non-technical professionals, as it has the potential to revolutionize various industries and provide innovative solutions to complex problems. With free AI courses and online certifications, individuals can acquire the necessary knowledge and skills to stay relevant in today’s rapidly evolving job market.

The Machine Learning Specialization by DeepLearning.AI and Stanford Online

The Machine Learning Specialization by DeepLearning.AI and Stanford Online is a foundational online program that provides a broad introduction to modern machine learning. This three-course specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field.

Other notable instructors include Eddy Shyu, curriculum product manager at DeepLearning.AI; Aarti Bagul, a curriculum engineer; and Geoff Ladwig, another top instructor at DeepLearning.AI.

The first course in the specialization is “Supervised Machine Learning: Regression and Classification,” which covers building machine learning models in Python using popular machine learning libraries NumPy and scikit-learn, and building and training supervised machine learning models for prediction and binary classification tasks, including linear regression and logistic regression.

The second course is “Advanced Learning Algorithms,” which teaches building and training a neural network with TensorFlow to perform multiclass classification, applying best practices for machine learning development so that your models generalize to data and tasks in the real world, and building and using decision trees and tree ensemble methods, including random forests and boosted trees.

The third and final course is “Unsupervised Learning, Recommenders, Reinforcement Learning,” which covers using unsupervised learning techniques for unsupervised learning, including clustering and anomaly detection, building recommender systems with a collaborative filtering approach and a content-based deep learning method, and building a deep reinforcement learning model.

By the end of this specialization, one will have mastered key concepts and gained practical know-how to quickly and powerfully apply machine learning to challenging real-world problems. If you’re looking to break into AI or build a career in machine learning, the Machine Learning Specialization is a great place to start.

CS50’s Introduction to Artificial Intelligence with Python by Harvard University

CS50’s Introduction to Artificial Intelligence with Python , offered by Harvard University, is an introductory course exploring modern artificial intelligence concepts and algorithms. The course is free on edX, but students can purchase a verified certificate for an additional fee. The instructors for the course are Gordon McKay, professor of the practice of computer science at Harvard University; Brian Yu, senior preceptor in computer science at Harvard University; and David Malan.

Students will dive into the ideas that give rise to technologies like game-playing engines, handwriting recognition and machine translation. This course teaches students how to incorporate machine learning concepts and algorithms into Python programs through a series of hands-on projects.

Students will gain exposure to the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence and machine learning. By the end of the course, students will have experience in libraries for machine learning, and knowledge of artificial intelligence principles that will enable them to design intelligent systems of their own.

AI For Everyone by Coursera in collaboration with DeepLearning.AI

AI for Everyone is an online course offered by Coursera in collaboration with DeepLearning.AI. This course is designed for non-technical learners who want to understand AI concepts and their practical applications. It provides an overview of AI and its impact on the world, covering the key concepts of machine learning, deep learning and neural networks.

The course is taught by Andrew Ng, a renowned AI expert and founder of DeepLearning.AI. He is also a co-founder of Coursera and has previously taught popular online courses on machine learning, neural networks and deep learning. The course consists of four modules, each covering a different aspect of AI. These are:

What is AI?
Building AI projects
Building AI in your company
AI and society

The course is self-paced and takes approximately 10 hours to complete. It includes video lectures, quizzes and case studies that allow students to apply the concepts they have learned using popular programming languages such as Python.

The course is free to audit on Coursera, and financial aid is available for those who cannot afford the fee. A certificate of completion is also available for a fee.

Machine Learning Crash Course with TensorFlow APIs by Google

The Machine Learning Crash Course with TensorFlow APIs is a free online course offered by Google. It’s designed for beginners who want to learn about machine learning and how to use TensorFlow, which is a popular open-source library for building and deploying machine learning models.

The course covers the following topics:

Introduction to machine learning and TensorFlow
Linear regression
Classification
Neural networks
Regularization
Training and validation
Convolutional neural networks
Natural language processing
Sequence models

Throughout the course, you’ll learn about different machine-learning techniques, and how to use TensorFlow application programming interfaces (APIs) to build and train models. The course also includes hands-on exercises and coding assignments, which will help you gain practical experience building and deploying machine learning models.

The course is available for free on Google’s website, and is self-paced so that you can learn at your own speed. Upon completion, you’ll receive a certificate of completion from Google.

Introduction to AI by Intel

The Intel® AI Fundamentals Course is an introductory-level course that teaches the fundamentals of artificial intelligence and its applications. It covers topics such as machine learning, deep learning, computer vision, natural language processing and more. The free and self-paced course includes modules that can be completed in any order.

The eight-week program includes lectures and exercises. Each week, students are expected to spend 90 minutes completing the coursework. The exercises are implemented in Python, so prior knowledge of the language is recommended, but students can also learn it along the way.

The course does not offer a certificate of completion, but students can earn badges for completing each module. The course is designed for software developers, data scientists and others interested in learning about AI.

Ready to join the AI revolution?

By taking advantage of the above resources, individuals can become part of the growing AI industry and contribute to shaping its future. Additionally, the ChatGPT Prompt Engineering for Developers course, developed in collaboration with OpenAI, offers developers the opportunity to learn how to use large language models (LLMs) to build powerful applications in a cost-effective and efficient manner. The course is taught by two renowned experts in the field of AI: Isa Fulford and Andrew Ng.

Whether a learner is a beginner or an advanced machine learning engineer, this course will provide the latest understanding of prompt engineering and best practices for using prompts for the latest LLM models. With hands-on experience, one will learn how to use LLM APIs for various tasks, including summarizing, inferring, transforming text and expanding, and building a custom chatbot. This course is free for a limited time, so don’t miss out on the opportunity to join the AI revolution.

Binance CEO, Coinbase exec feature in Masterclass crypto crash-course

December 8, 2022 Coin Telegraph

Coin Telegraph

Industry experts and one skeptical economist tackle the world of crypto, blockchain and Web3 in a new series from online learning platform Masterclass.

For the uninitiated, the world of cryptocurrencies and blockchain technology can be daunting, confusing and difficult to comprehend. Three industry experts and a skeptical economist explore the past, present and future of the burgeoning technology in a new online learning series.

Masterclass is a web-based education platform that offers “classes” from subject matter experts in their respective spheres of influence. You can learn how to cook with Gordon Ramsay, explore the art of acting with Natalie Portman or master the tennis racket with Serena Williams.

Its newly launched series on cryptocurrencies, blockchain and Web3 technology follows in the same vein. Binance CEO Changpeng “CZ” Zhao, A16z general partner Chris Dixon, Coinbase president Emilie Choi and Nobel laureate economist Paul Krugman tackle the ins and outs of the subject that is gradually transforming the way we transact and use the internet.

Cointelegraph was offered exclusive access to the series which starts off with an introduction to cryptocurrencies and a macro view of blockchain technology’s inception. In typical Masterclass style, the episodes are superbly produced, with the trusty experts giving anecdotes and answering the most pertinent questions of newcomers to the space.

Zhao encapsulates the evolution of the technology by highlighting how the internet allowed humanity to transfer information, while blockchain builds upon that by powering the transfer of value. Meanwhile, Choi provided a more pertinent insight, pressing home the power of decentralization in giving control back to individuals:

“Crypto is by default inclusive as long as you have some sort of internet connection. This is particularly powerful for people who have been locked out of the traditional financial system.”

Dixon is also a prominent voice through the series, lending his expertise as a technology entrepreneur and prominent cryptocurrency and Web3 evangelist. His introductory thoughts in the series set the tone for the overarching theme of Web3’s influence on the ever-evolving internet: “The big question now is how will those new networks in the next year of the internet be created, who will own them, who will control them and who will make the money.”

The history of crypto — Rooted in Bitcoin

Zhao takes a central role as Masterclass covers the history of cryptocurrency. Rooted in cryptography and the need to solve the Byzantine General’s Problem, Zha unpacks these concepts before touching on the enigma that is Bitcoin’s (BTC) pseudonymous creator Satoshi Nakamoto.

With the 2008 financial crisis as a trigger point, the CEO points to the publication of the Bitcoin white paper as a seminal moment for the cryptocurrency and Web3 landscape that we know and use today. The famous Bitcoin pizza is also featured, given its importance as the first commercial transaction using Bitcoin.

The development of Ethereum is another focal point as a means for entrepreneurs to enter the cryptocurrency ecosystem thanks to smart contract functionality and the ability to issue ERC-20 tokens.

The concept and appeal of “freedom” are touched on by both Zhao and Dixon, with the former pointing to this aspect being desirable to both libertarians and “hardcore anarchists.” Dixon wraps up the class by quoting writer William Gibson:

“The future is already here, it’s just not evenly distributed.”

His belief is that crypto is still a grassroots internet and technology movement. But tech companies and financial institutions don’t like it, which puts paid to the quote above.

Web3: Read, write and own

Web3 is becoming a ubiquitous concept, but the influence of cryptocurrencies and blockchain technology may well be lost on some. Masterclass does a good job bringing the pieces back together as Choi highlights the main differences between Web1, Web2 and Web3.

Web1 represents the early internet, where websites were read-only landing pages governed by open protocols and users simply consumed information. The rise of Web2 in the early 2000s introduced read-and-write functionality, which Choi described as a paradigm shift:

“Users are the product, central companies dictated rules and held control of the data and content users created.”

Dixon gets stuck in at this point, highlighting the rise of Google, Facebook, Amazon and Apple unlocking the power of technology, doing things you can’t do with TV, magazines and other mediums. The result was the consolidation of power and economic control between a handful of major companies:

“What that means for creators, devs and entrepreneurs is that instead of building on open systems, you were dependent on those companies to acquire and maintain audiences to sell things.”

This is where Web3 enters the fray, democratizing not just information but publishing and ownership. It is inherently community-owned and operated, with token applications proliferating new Web3 applications and concepts.

Choi sums it up succinctly, with cryptocurrency forming the backend infrastructure that powers Web3. Web3, she contends, is more about front-end apps that become more robust in a crypto-powered world:

“If you look at the Metaverse as a Web3 experience, crypto is the central plumbing for tokens and wallets.”

Perhaps most importantly, Dixon weighs in on why Web3 matters considering three simple questions. Who makes the money? Who controls the content? Who controls the network? Web3’s value is the transfer of true ownership from the few to the many:

“Is it companies or communities of people? The internet is clearly the most important tech innovation still developing today. It affects culture, politics, economics and our daily lives.”

A separate episode on nonfungible tokens (NFTs) sees Dixon dive head-first into the popularity of digital collectibles and tokenized assets. Sport-focused digital collectibles, digital artwork changing the way artists own, share and earn from their creations and musicians making use of NFTs to engage with fans are all notable use cases highlighted in the series.

In a first for Masterclass, economist Paul Krugman hosts a thought-provoking debate with Zhao, posing a host of pertinent questions that address perceived problems with crypto from a mainstream lens.

Krugman’s role as the skeptic economist is measured but assertive, with questions ranging from what problems cryptocurrencies solve, why regular financial institutions and banks should adopt blockchain and how these systems can power fast and cheap transactions.

All in all, the series serves up introductory, lecture-style chapters touching on the basic principles of the industry. Without getting technical, core concepts that have influenced the development of cryptocurrencies, blockchain and Web3 innovations are unpacked in an easy-to-digest form.

Common questions of skeptics are addressed as well, presenting a balanced macro-view of the space that might just lead intrigued viewers down a path of further individual discovery of all things crypto.

The views, thoughts and opinions expressed here do not necessarily reflect or represent the views and opinions of Cointelegraph.

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