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| chatgpt prompt engineering for developers certificate: The Secrets of ChatGPT Prompt Engineering for Non-Developers Cea West, Become a prompt engineer with the help of this practical guide. With broad applicability across various topics such as copywriting, SEO, book writing, fiction, and non-fiction, this comprehensive guide provides valuable insights for anyone interested in exploring the art of prompt engineering. Learn practical strategies to monetize your use of ChatGPT while enhancing your writing and communication skills. Boost the efficiency and productivity of content creation by implementing the actionable knowledge gained from this book. |
| chatgpt prompt engineering for developers certificate: Prompt Engineering Using ChatGPT Mehrzad Tabatabaian, 2024-06-17 This book provides a structured framework for exploring various aspects of prompt engineering for ChatGPT, from foundational principles to advanced techniques, real-world applications, and ethical considerations. It aims to guide readers in effectively harnessing the capabilities of ChatGPT through well-crafted prompts to achieve their goals. The digital age has ushered in a new era of communication, one where the boundaries between human and machine are becoming increasingly blurred. Artificial Intelligence (AI) technology, in its relentless evolution, has given rise to remarkable language models that can understand and generate human-like text. Prompt Engineering for ChatGPT, demystifies the intricacies of this ground breaking technology, offering insights and strategies to harness its capabilities. |
| chatgpt prompt engineering for developers certificate: Learning How to Learn Barbara Oakley, PhD, Terrence Sejnowski, PhD, Alistair McConville, 2018-08-07 A surprisingly simple way for students to master any subject--based on one of the world's most popular online courses and the bestselling book A Mind for Numbers A Mind for Numbers and its wildly popular online companion course Learning How to Learn have empowered more than two million learners of all ages from around the world to master subjects that they once struggled with. Fans often wish they'd discovered these learning strategies earlier and ask how they can help their kids master these skills as well. Now in this new book for kids and teens, the authors reveal how to make the most of time spent studying. We all have the tools to learn what might not seem to come naturally to us at first--the secret is to understand how the brain works so we can unlock its power. This book explains: Why sometimes letting your mind wander is an important part of the learning process How to avoid rut think in order to think outside the box Why having a poor memory can be a good thing The value of metaphors in developing understanding A simple, yet powerful, way to stop procrastinating Filled with illustrations, application questions, and exercises, this book makes learning easy and fun. |
| chatgpt prompt engineering for developers certificate: Python for Everybody Charles R. Severance, 2016-04-09 Python for Everybody is designed to introduce students to programming and software development through the lens of exploring data. You can think of the Python programming language as your tool to solve data problems that are beyond the capability of a spreadsheet.Python is an easy to use and easy to learn programming language that is freely available on Macintosh, Windows, or Linux computers. So once you learn Python you can use it for the rest of your career without needing to purchase any software.This book uses the Python 3 language. The earlier Python 2 version of this book is titled Python for Informatics: Exploring Information.There are free downloadable electronic copies of this book in various formats and supporting materials for the book at www.pythonlearn.com. The course materials are available to you under a Creative Commons License so you can adapt them to teach your own Python course. |
| chatgpt prompt engineering for developers certificate: Data Science on AWS Chris Fregly, Antje Barth, 2021-04-07 With this practical book, AI and machine learning practitioners will learn how to successfully build and deploy data science projects on Amazon Web Services. The Amazon AI and machine learning stack unifies data science, data engineering, and application development to help level upyour skills. This guide shows you how to build and run pipelines in the cloud, then integrate the results into applications in minutes instead of days. Throughout the book, authors Chris Fregly and Antje Barth demonstrate how to reduce cost and improve performance. Apply the Amazon AI and ML stack to real-world use cases for natural language processing, computer vision, fraud detection, conversational devices, and more Use automated machine learning to implement a specific subset of use cases with SageMaker Autopilot Dive deep into the complete model development lifecycle for a BERT-based NLP use case including data ingestion, analysis, model training, and deployment Tie everything together into a repeatable machine learning operations pipeline Explore real-time ML, anomaly detection, and streaming analytics on data streams with Amazon Kinesis and Managed Streaming for Apache Kafka Learn security best practices for data science projects and workflows including identity and access management, authentication, authorization, and more |
| chatgpt prompt engineering for developers certificate: Machine Learning in Finance Matthew F. Dixon, Igor Halperin, Paul Bilokon, 2020-07-01 This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and computational disciplines in quantitative finance, such as financial econometrics and discrete time stochastic control, with an emphasis on how theory and hypothesis tests inform the choice of algorithm for financial data modeling and decision making. With the trend towards increasing computational resources and larger datasets, machine learning has grown into an important skillset for the finance industry. This book is written for advanced graduate students and academics in financial econometrics, mathematical finance and applied statistics, in addition to quants and data scientists in the field of quantitative finance. Machine Learning in Finance: From Theory to Practice is divided into three parts, each part covering theory and applications. The first presents supervised learning for cross-sectional data from both a Bayesian and frequentist perspective. The more advanced material places a firm emphasis on neural networks, including deep learning, as well as Gaussian processes, with examples in investment management and derivative modeling. The second part presents supervised learning for time series data, arguably the most common data type used in finance with examples in trading, stochastic volatility and fixed income modeling. Finally, the third part presents reinforcement learning and its applications in trading, investment and wealth management. Python code examples are provided to support the readers' understanding of the methodologies and applications. The book also includes more than 80 mathematical and programming exercises, with worked solutions available to instructors. As a bridge to research in this emergent field, the final chapter presents the frontiers of machine learning in finance from a researcher's perspective, highlighting how many well-known concepts in statistical physics are likely to emerge as important methodologies for machine learning in finance. |
| chatgpt prompt engineering for developers certificate: Artificial Intelligence with Python Prateek Joshi, 2017-01-27 Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application. |
| chatgpt prompt engineering for developers certificate: Teach Your Kids to Code Bryson Payne, 2015-04-01 Teach Your Kids to Code is a parent's and teacher's guide to teaching kids basic programming and problem solving using Python, the powerful language used in college courses and by tech companies like Google and IBM. Step-by-step explanations will have kids learning computational thinking right away, while visual and game-oriented examples hold their attention. Friendly introductions to fundamental programming concepts such as variables, loops, and functions will help even the youngest programmers build the skills they need to make their own cool games and applications. Whether you've been coding for years or have never programmed anything at all, Teach Your Kids to Code will help you show your young programmer how to: –Explore geometry by drawing colorful shapes with Turtle graphics –Write programs to encode and decode messages, play Rock-Paper-Scissors, and calculate how tall someone is in Ping-Pong balls –Create fun, playable games like War, Yahtzee, and Pong –Add interactivity, animation, and sound to their apps Teach Your Kids to Code is the perfect companion to any introductory programming class or after-school meet-up, or simply your educational efforts at home. Spend some fun, productive afternoons at the computer with your kids—you can all learn something! |
| chatgpt prompt engineering for developers certificate: Deep Learning for Coders with fastai and PyTorch Jeremy Howard, Sylvain Gugger, 2020-06-29 Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala |
| chatgpt prompt engineering for developers certificate: Natural Language Processing with TensorFlow Thushan Ganegedara, 2018-05-31 Write modern natural language processing applications using deep learning algorithms and TensorFlow Key Features Focuses on more efficient natural language processing using TensorFlow Covers NLP as a field in its own right to improve understanding for choosing TensorFlow tools and other deep learning approaches Provides choices for how to process and evaluate large unstructured text datasets Learn to apply the TensorFlow toolbox to specific tasks in the most interesting field in artificial intelligence Book Description Natural language processing (NLP) supplies the majority of data available to deep learning applications, while TensorFlow is the most important deep learning framework currently available. Natural Language Processing with TensorFlow brings TensorFlow and NLP together to give you invaluable tools to work with the immense volume of unstructured data in today’s data streams, and apply these tools to specific NLP tasks. Thushan Ganegedara starts by giving you a grounding in NLP and TensorFlow basics. You'll then learn how to use Word2vec, including advanced extensions, to create word embeddings that turn sequences of words into vectors accessible to deep learning algorithms. Chapters on classical deep learning algorithms, like convolutional neural networks (CNN) and recurrent neural networks (RNN), demonstrate important NLP tasks as sentence classification and language generation. You will learn how to apply high-performance RNN models, like long short-term memory (LSTM) cells, to NLP tasks. You will also explore neural machine translation and implement a neural machine translator. After reading this book, you will gain an understanding of NLP and you'll have the skills to apply TensorFlow in deep learning NLP applications, and how to perform specific NLP tasks. What you will learn Core concepts of NLP and various approaches to natural language processing How to solve NLP tasks by applying TensorFlow functions to create neural networks Strategies to process large amounts of data into word representations that can be used by deep learning applications Techniques for performing sentence classification and language generation using CNNs and RNNs About employing state-of-the art advanced RNNs, like long short-term memory, to solve complex text generation tasks How to write automatic translation programs and implement an actual neural machine translator from scratch The trends and innovations that are paving the future in NLP Who this book is for This book is for Python developers with a strong interest in deep learning, who want to learn how to leverage TensorFlow to simplify NLP tasks. Fundamental Python skills are assumed, as well as some knowledge of machine learning and undergraduate-level calculus and linear algebra. No previous natural language processing experience required, although some background in NLP or computational linguistics will be helpful. |
| chatgpt prompt engineering for developers certificate: AI and Machine Learning for Coders Laurence Moroney, 2020-10-01 If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics. You'll understand how to implement the most common scenarios in machine learning, such as computer vision, natural language processing (NLP), and sequence modeling for web, mobile, cloud, and embedded runtimes. Most books on machine learning begin with a daunting amount of advanced math. This guide is built on practical lessons that let you work directly with the code. You'll learn: How to build models with TensorFlow using skills that employers desire The basics of machine learning by working with code samples How to implement computer vision, including feature detection in images How to use NLP to tokenize and sequence words and sentences Methods for embedding models in Android and iOS How to serve models over the web and in the cloud with TensorFlow Serving |
| chatgpt prompt engineering for developers certificate: The Science of Success: What Researchers Know that You Should Know Paula J. Caproni, 2016-12-08 Short description. |
| chatgpt prompt engineering for developers certificate: Fundamentals of Deep Learning Nikhil Buduma, Nicholas Locascio, 2017-05-25 With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that’s paving the way for modern machine learning. In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field. Companies such as Google, Microsoft, and Facebook are actively growing in-house deep-learning teams. For the rest of us, however, deep learning is still a pretty complex and difficult subject to grasp. If you’re familiar with Python, and have a background in calculus, along with a basic understanding of machine learning, this book will get you started. Examine the foundations of machine learning and neural networks Learn how to train feed-forward neural networks Use TensorFlow to implement your first neural network Manage problems that arise as you begin to make networks deeper Build neural networks that analyze complex images Perform effective dimensionality reduction using autoencoders Dive deep into sequence analysis to examine language Learn the fundamentals of reinforcement learning |
| chatgpt prompt engineering for developers certificate: Advanced Deep Learning with Keras Rowel Atienza, 2018-10-31 Understanding and coding advanced deep learning algorithms with the most intuitive deep learning library in existence Key Features Explore the most advanced deep learning techniques that drive modern AI results Implement deep neural networks, autoencoders, GANs, VAEs, and deep reinforcement learning A wide study of GANs, including Improved GANs, Cross-Domain GANs, and Disentangled Representation GANs Book DescriptionRecent developments in deep learning, including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Deep Reinforcement Learning (DRL) are creating impressive AI results in our news headlines - such as AlphaGo Zero beating world chess champions, and generative AI that can create art paintings that sell for over $400k because they are so human-like. Advanced Deep Learning with Keras is a comprehensive guide to the advanced deep learning techniques available today, so you can create your own cutting-edge AI. Using Keras as an open-source deep learning library, you'll find hands-on projects throughout that show you how to create more effective AI with the latest techniques. The journey begins with an overview of MLPs, CNNs, and RNNs, which are the building blocks for the more advanced techniques in the book. You’ll learn how to implement deep learning models with Keras and TensorFlow 1.x, and move forwards to advanced techniques, as you explore deep neural network architectures, including ResNet and DenseNet, and how to create autoencoders. You then learn all about GANs, and how they can open new levels of AI performance. Next, you’ll get up to speed with how VAEs are implemented, and you’ll see how GANs and VAEs have the generative power to synthesize data that can be extremely convincing to humans - a major stride forward for modern AI. To complete this set of advanced techniques, you'll learn how to implement DRL such as Deep Q-Learning and Policy Gradient Methods, which are critical to many modern results in AI.What you will learn Cutting-edge techniques in human-like AI performance Implement advanced deep learning models using Keras The building blocks for advanced techniques - MLPs, CNNs, and RNNs Deep neural networks – ResNet and DenseNet Autoencoders and Variational Autoencoders (VAEs) Generative Adversarial Networks (GANs) and creative AI techniques Disentangled Representation GANs, and Cross-Domain GANs Deep reinforcement learning methods and implementation Produce industry-standard applications using OpenAI Gym Deep Q-Learning and Policy Gradient Methods Who this book is for Some fluency with Python is assumed. As an advanced book, you'll be familiar with some machine learning approaches, and some practical experience with DL will be helpful. Knowledge of Keras or TensorFlow 1.x is not required but would be helpful. |
| chatgpt prompt engineering for developers certificate: Getting Started with Natural Language Processing Ekaterina Kochmar, 2022-11-15 Hit the ground running with this in-depth introduction to the NLP skills and techniques that allow your computers to speak human. In Getting Started with Natural Language Processing you’ll learn about: Fundamental concepts and algorithms of NLP Useful Python libraries for NLP Building a search algorithm Extracting information from raw text Predicting sentiment of an input text Author profiling Topic labeling Named entity recognition Getting Started with Natural Language Processing is an enjoyable and understandable guide that helps you engineer your first NLP algorithms. Your tutor is Dr. Ekaterina Kochmar, lecturer at the University of Bath, who has helped thousands of students take their first steps with NLP. Full of Python code and hands-on projects, each chapter provides a concrete example with practical techniques that you can put into practice right away. If you’re a beginner to NLP and want to upgrade your applications with functions and features like information extraction, user profiling, and automatic topic labeling, this is the book for you. About the technology From smart speakers to customer service chatbots, apps that understand text and speech are everywhere. Natural language processing, or NLP, is the key to this powerful form of human/computer interaction. And a new generation of tools and techniques make it easier than ever to get started with NLP! About the book Getting Started with Natural Language Processing teaches you how to upgrade user-facing applications with text and speech-based features. From the accessible explanations and hands-on examples in this book you’ll learn how to apply NLP to sentiment analysis, user profiling, and much more. As you go, each new project builds on what you’ve previously learned, introducing new concepts and skills. Handy diagrams and intuitive Python code samples make it easy to get started—even if you have no background in machine learning! What's inside Fundamental concepts and algorithms of NLP Extracting information from raw text Useful Python libraries Topic labeling Building a search algorithm About the reader You’ll need basic Python skills. No experience with NLP required. About the author Ekaterina Kochmar is a lecturer at the Department of Computer Science of the University of Bath, where she is part of the AI research group. Table of Contents 1 Introduction 2 Your first NLP example 3 Introduction to information search 4 Information extraction 5 Author profiling as a machine-learning task 6 Linguistic feature engineering for author profiling 7 Your first sentiment analyzer using sentiment lexicons 8 Sentiment analysis with a data-driven approach 9 Topic analysis 10 Topic modeling 11 Named-entity recognition |
| chatgpt prompt engineering for developers certificate: Modern Robotics Kevin M. Lynch, Frank C. Park, 2017-05-25 A modern and unified treatment of the mechanics, planning, and control of robots, suitable for a first course in robotics. |
| chatgpt prompt engineering for developers certificate: Learning TensorFlow Tom Hope, Yehezkel S. Resheff, Itay Lieder, 2017-08-09 Roughly inspired by the human brain, deep neural networks trained with large amounts of data can solve complex tasks with unprecedented accuracy. This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for computer vision, natural language processing (NLP), speech recognition, and general predictive analytics. Authors Tom Hope, Yehezkel Resheff, and Itay Lieder provide a hands-on approach to TensorFlow fundamentals for a broad technical audience—from data scientists and engineers to students and researchers. You’ll begin by working through some basic examples in TensorFlow before diving deeper into topics such as neural network architectures, TensorBoard visualization, TensorFlow abstraction libraries, and multithreaded input pipelines. Once you finish this book, you’ll know how to build and deploy production-ready deep learning systems in TensorFlow. Get up and running with TensorFlow, rapidly and painlessly Learn how to use TensorFlow to build deep learning models from the ground up Train popular deep learning models for computer vision and NLP Use extensive abstraction libraries to make development easier and faster Learn how to scale TensorFlow, and use clusters to distribute model training Deploy TensorFlow in a production setting |
| chatgpt prompt engineering for developers certificate: WSO2 Developer's Guide Fidel Prieto Estrada, Ramon Garrido Lazaro, 2017-09-29 WSO2 Made Simple – dive deep into the core concepts of WSO2 to overcome the challenges faced while using the Enterprise Integrator About This Book Design, create, and publish services in the WSO2 technology Integrate the WSO2 Enterprise Integrator with other components and servers Log and test deployed services Who This Book Is For If you are a Java solutions architect or developer and are keen to understand how to build enterprise applications with WSO2, this book is for you. No prior knowledge of WSO2 is expected. What You Will Learn Configure WSO2 Enterprise Integrator server in a production environment Create SOAP Proxies and REST APIs Interact with WSO2 Message Broker Write services using the new language: Ballerina Schedule automatic tasks for the services you create Manage log messages depending on the log level of the system Integrate with social networks such as Twitter, Facebook, Instagram, and Yammer Test SOAP Services using the Tryit feature and SoapUI tool Work with Quality of Services In Detail WSO2 Enterprise Integrator brings together the most powerful servers provided by the WSO2 company for your SOA infrastructure. As an Enterprise Service Bus (ESB), WSO2 Enterprise Integrator provides greater flexibility and agility to meet growing enterprise demands, whereas, as a Data Services Server (DSS), it provides an easy-to-use platform for integrating data stores, creating composite views across different data sources, and hosting data services. Using real-world scenarios, this book helps you build a solid foundation in developing enterprise applications with powerful data integration capabilities using the WSO2 servers. The book gets you started by brushing up your knowledge about SOA architecture and how it can be implemented through WSO2. It will help build your expertise with the core concepts of ESB such as building proxies, sequences, endpoints, and how to work with these in WSO2. Going further, you will also get well-acquainted with DSS data service concepts such as configuring data services, tasks, events, testing, and much more. The book will also cover API management techniques. Along with ESB and DSS, you will also learn about business process servers, the rules server and other components that together provide the control and robustness your enterprise applications will need. With practical use cases, the book covers typical daily scenarios you will come across while using these servers to give you hands-on experience. Style and approach The book is a complete guide and helps you get the right start—from understanding SOA architectures to getting valuable experience with two important integration servers such as ESB and DSS. It will include some real-world practical scenarios to help you master the best practices followed right across the industry and overcome the challenges you're likely to face on a daily basis. |
| chatgpt prompt engineering for developers certificate: Good with Words Patrick Barry, 2019-05-31 If your success at work or in school depends on your ability to communicate persuasively in writing, you'll want to get Good with Words. Based on a course that law students at the University of Michigan and the University of Chicago have called outstanding, A-M-A-Z-I-N-G, and the best course I have ever taken, the book brings together a collection of concepts, exercises, and examples that have also helped improve the advocacy skills of people pursuing careers in many other fields--from marketing, to management, to medicine. There is nobody better than Patrick Barry when it comes to breaking down how to write and edit. His techniques don't just make you sound better. They make you think better. I'm jealous of the people who get to take his classes. --Professor Lisa Bernstein, University of Chicago Law School and Oxford University Center for Corporate Regulation Whenever I use Patrick Barry's materials in my class, the student reaction is the same: 'We want more of them.' --Professor Dave Babbe, UCLA School of Law Working one-on-one with Patrick Barry should be mandatory for all lawyers, regardless of seniority. This book is the next best thing. --Purvi Patel, Partner at Morrison Foerster LLP I am proud to say that, when it comes to writing, I speak Patrick Barry. What I mean is that I use, pretty much every day, the writing vocabulary and techniques he offers in this great book. So read it. Share it. And then, if you can, teach it. There are a lot of good causes in the world that could use a new generation of great advocates. --Professor Bridgette Carr, Assistant Dean of Strategic Initiatives and Director of the Human Trafficking Clinic at the University of Michigan Law School Patrick Barry is my secret weapon. I use his techniques every time I write, and I also teach them to all my students. --Professor Shai Dothan, Copenhagen Faculty of Law I know the materials in this book were originally created for lawyers and law students. But I actually find them really helpful for doctors as well, given that a lot of what I do every day depends on effective communication. There is a tremendous upside to becoming 'Good with Words. --Dr. Ramzi Abboud, Washington University School of Medicine in St. Louis. |
| chatgpt prompt engineering for developers certificate: Deep Learning with PyTorch Luca Pietro Giovanni Antiga, Eli Stevens, Thomas Viehmann, 2020-07-01 “We finally have the definitive treatise on PyTorch! It covers the basics and abstractions in great detail. I hope this book becomes your extended reference document.” —Soumith Chintala, co-creator of PyTorch Key Features Written by PyTorch’s creator and key contributors Develop deep learning models in a familiar Pythonic way Use PyTorch to build an image classifier for cancer detection Diagnose problems with your neural network and improve training with data augmentation Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About The Book Every other day we hear about new ways to put deep learning to good use: improved medical imaging, accurate credit card fraud detection, long range weather forecasting, and more. PyTorch puts these superpowers in your hands. Instantly familiar to anyone who knows Python data tools like NumPy and Scikit-learn, PyTorch simplifies deep learning without sacrificing advanced features. It’s great for building quick models, and it scales smoothly from laptop to enterprise. Deep Learning with PyTorch teaches you to create deep learning and neural network systems with PyTorch. This practical book gets you to work right away building a tumor image classifier from scratch. After covering the basics, you’ll learn best practices for the entire deep learning pipeline, tackling advanced projects as your PyTorch skills become more sophisticated. All code samples are easy to explore in downloadable Jupyter notebooks. What You Will Learn Understanding deep learning data structures such as tensors and neural networks Best practices for the PyTorch Tensor API, loading data in Python, and visualizing results Implementing modules and loss functions Utilizing pretrained models from PyTorch Hub Methods for training networks with limited inputs Sifting through unreliable results to diagnose and fix problems in your neural network Improve your results with augmented data, better model architecture, and fine tuning This Book Is Written For For Python programmers with an interest in machine learning. No experience with PyTorch or other deep learning frameworks is required. About The Authors Eli Stevens has worked in Silicon Valley for the past 15 years as a software engineer, and the past 7 years as Chief Technical Officer of a startup making medical device software. Luca Antiga is co-founder and CEO of an AI engineering company located in Bergamo, Italy, and a regular contributor to PyTorch. Thomas Viehmann is a Machine Learning and PyTorch speciality trainer and consultant based in Munich, Germany and a PyTorch core developer. Table of Contents PART 1 - CORE PYTORCH 1 Introducing deep learning and the PyTorch Library 2 Pretrained networks 3 It starts with a tensor 4 Real-world data representation using tensors 5 The mechanics of learning 6 Using a neural network to fit the data 7 Telling birds from airplanes: Learning from images 8 Using convolutions to generalize PART 2 - LEARNING FROM IMAGES IN THE REAL WORLD: EARLY DETECTION OF LUNG CANCER 9 Using PyTorch to fight cancer 10 Combining data sources into a unified dataset 11 Training a classification model to detect suspected tumors 12 Improving training with metrics and augmentation 13 Using segmentation to find suspected nodules 14 End-to-end nodule analysis, and where to go next PART 3 - DEPLOYMENT 15 Deploying to production |
| chatgpt prompt engineering for developers certificate: Machine Learning with R Brett Lantz, 2013-10-25 Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required. |
| chatgpt prompt engineering for developers certificate: Learn to Program Chris Pine, 2021-06-17 It's easier to learn how to program a computer than it has ever been before. Now everyone can learn to write programs for themselves - no previous experience is necessary. Chris Pine takes a thorough, but lighthearted approach that teaches you the fundamentals of computer programming, with a minimum of fuss or bother. Whether you are interested in a new hobby or a new career, this book is your doorway into the world of programming. Computers are everywhere, and being able to program them is more important than it has ever been. But since most books on programming are written for other programmers, it can be hard to break in. At least it used to be. Chris Pine will teach you how to program. You'll learn to use your computer better, to get it to do what you want it to do. Starting with small, simple one-line programs to calculate your age in seconds, you'll see how to write interactive programs, to use APIs to fetch live data from the internet, to rename your photos from your digital camera, and more. You'll learn the same technology used to drive modern dynamic websites and large, professional applications. Whether you are looking for a fun new hobby or are interested in entering the tech world as a professional, this book gives you a solid foundation in programming. Chris teaches the basics, but also shows you how to think like a programmer. You'll learn through tons of examples, and through programming challenges throughout the book. When you finish, you'll know how and where to learn more - you'll be on your way. What You Need: All you need to learn how to program is a computer (Windows, macOS, or Linux) and an internet connection. Chris Pine will lead you through setting set up with the software you will need to start writing programs of your own. |
| chatgpt prompt engineering for developers certificate: Dive Into Deep Learning Joanne Quinn, Joanne McEachen, Michael Fullan, Mag Gardner, Max Drummy, 2019-07-15 The leading experts in system change and learning, with their school-based partners around the world, have created this essential companion to their runaway best-seller, Deep Learning: Engage the World Change the World. This hands-on guide provides a roadmap for building capacity in teachers, schools, districts, and systems to design deep learning, measure progress, and assess conditions needed to activate and sustain innovation. Dive Into Deep Learning: Tools for Engagement is rich with resources educators need to construct and drive meaningful deep learning experiences in order to develop the kind of mindset and know-how that is crucial to becoming a problem-solving change agent in our global society. Designed in full color, this easy-to-use guide is loaded with tools, tips, protocols, and real-world examples. It includes: • A framework for deep learning that provides a pathway to develop the six global competencies needed to flourish in a complex world — character, citizenship, collaboration, communication, creativity, and critical thinking. • Learning progressions to help educators analyze student work and measure progress. • Learning design rubrics, templates and examples for incorporating the four elements of learning design: learning partnerships, pedagogical practices, learning environments, and leveraging digital. • Conditions rubrics, teacher self-assessment tools, and planning guides to help educators build, mobilize, and sustain deep learning in schools and districts. Learn about, improve, and expand your world of learning. Put the joy back into learning for students and adults alike. Dive into deep learning to create learning experiences that give purpose, unleash student potential, and transform not only learning, but life itself. |
| chatgpt prompt engineering for developers certificate: Zero to AI Nicolò Valigi, Gianluca Mauro, 2020-05-19 Summary How can artificial intelligence transform your business? In Zero to AI, you’ll explore a variety of practical AI applications you can use to improve customer experiences, optimize marketing, help you cut costs, and more. In this engaging guide written for business leaders and technology pros alike, authors and AI experts Nicolò Valigi and Gianluca Mauro use fascinating projects, hands-on activities, and real-world explanations to make it clear how your business can benefit from AI. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology There’s no doubt that artificial intelligence has made some impressive headlines recently, from besting chess and Go grand masters to producing uncanny deep fakes that blur the lines of reality. But what can AI do for you? If you want to understand how AI will impact your business before you invest your time and money, this book is for you. About the book Zero to AI uses clear examples and jargon-free explanations to show the practical benefits of AI. Each chapter explores a real-world case study demonstrating how companies like Google and Netflix use AI to shape their industries. You begin at the beginning, with a primer on core AI concepts and realistic business outcomes. To help you prepare for the transition, the book breaks down a successful AI implementation, including advice on hiring the right team and making decisions about resources, risks, and costs. What's inside Identifying where AI can help your organization Designing an AI strategy Evaluating project scope and business impact Using AI to boost conversion rates, curate content, and analyze feedback Understanding how modern AI works and what it can/can’t do About the reader For anyone who wants to gain an understanding of practical artificial intelligence and learn how to design and develop projects with high business impact. About the author Gianluca Mauro and Nicolò Valigi are the cofounders of AI Academy, a company specializing in AI trainings and consulting. Table of Contents: 1. An introduction to artificial intelligence PART 1 - UNDERSTANDING AI 2. Artificial intelligence for core business data 3. AI for sales and marketing 4. AI for media 5. AI for natural language 6. AI for content curation and community building PART 2 - BUILDING AI 7. Ready—finding AI opportunities 8. Set—preparing data, technology, and people 9. Go—AI implementation strategy 10. What lies ahead |
| chatgpt prompt engineering for developers certificate: Data Science for Marketing Analytics Mirza Rahim Baig, Gururajan Govindan, Vishwesh Ravi Shrimali, 2021-09-07 Turbocharge your marketing plans by making the leap from simple descriptive statistics in Excel to sophisticated predictive analytics with the Python programming language Key FeaturesUse data analytics and machine learning in a sales and marketing contextGain insights from data to make better business decisionsBuild your experience and confidence with realistic hands-on practiceBook Description Unleash the power of data to reach your marketing goals with this practical guide to data science for business. This book will help you get started on your journey to becoming a master of marketing analytics with Python. You'll work with relevant datasets and build your practical skills by tackling engaging exercises and activities that simulate real-world market analysis projects. You'll learn to think like a data scientist, build your problem-solving skills, and discover how to look at data in new ways to deliver business insights and make intelligent data-driven decisions. As well as learning how to clean, explore, and visualize data, you'll implement machine learning algorithms and build models to make predictions. As you work through the book, you'll use Python tools to analyze sales, visualize advertising data, predict revenue, address customer churn, and implement customer segmentation to understand behavior. By the end of this book, you'll have the knowledge, skills, and confidence to implement data science and machine learning techniques to better understand your marketing data and improve your decision-making. What you will learnLoad, clean, and explore sales and marketing data using pandasForm and test hypotheses using real data sets and analytics toolsVisualize patterns in customer behavior using MatplotlibUse advanced machine learning models like random forest and SVMUse various unsupervised learning algorithms for customer segmentationUse supervised learning techniques for sales predictionEvaluate and compare different models to get the best outcomesOptimize models with hyperparameter tuning and SMOTEWho this book is for This marketing book is for anyone who wants to learn how to use Python for cutting-edge marketing analytics. Whether you're a developer who wants to move into marketing, or a marketing analyst who wants to learn more sophisticated tools and techniques, this book will get you on the right path. Basic prior knowledge of Python and experience working with data will help you access this book more easily. |
| chatgpt prompt engineering for developers certificate: Beginning Photo Retouching and Restoration Using GIMP Phillip Whitt, 2014-12-20 Beginning Photo Retouching & Restoration Using GIMP teaches the reader how to achieve professional results using this high end image editor. You'll learn how to do everything from making dull images pop to resurrecting badly damaged photographs deemed beyond any hope of rescue. There's no need to shell out good money month after month for the big name software package. GIMP 2.8 is a world-class image editor that wields almost as much power, and is completely free! Learning the art of photo retouching and restoration is fun and rewarding. Reclaim those treasured images from the ravages of time and neglect, and pass them on to future generations. Beginning Photo Retouching & Restoration Using GIMP will provide you with a wide array of editing exercises to help you develop a high degree of proficiency. Whether you are the designated family archivist wanting to preserve your family history, or a professional photographer with a desire to add an extra revenue generating service, this book will be an invaluable aid. • Shows how to acquire the best scans and digitize large photographs. • Teaches you how to digitally repair damaged prints, correct color shifts, reclaim lost detail-even colorize black and white images. • Offers great tips on how to maintain and preserve your newly printed restored photographs, and how to properly store originals. |
| chatgpt prompt engineering for developers certificate: Prompt Engineering for Everyone David Scott Bernstein, 2023-08-15 **Discover the Power of Prompt Engineering to Unlock ChatGPT**Unlock the full potential of ChatGPT and AI-language models with *Prompt Engineering for Everyone*, a groundbreaking guide co-authored by ChatGPT itself. This comprehensive book takes you on a transformative journey into the realm of AI language models, providing practical techniques to craft compelling prompts and revolutionize your interactions with artificial intelligence.From essential prompt writing skills to advanced techniques, this book equips you with the tools to optimize and evaluate prompts, tackle complex topics, and leverage multiple types of prompts. Gain clarity and precision in your AI interactions by learning the art of crafting clear and effective prompts, while understanding the ethics of prompt writing.Step into the future of AI technology with visionary concepts and stay ahead in the rapidly evolving landscape of prompt engineering. Explore the bonus pack for essential prompts and elevate your prompt engineering skills. Get ready to unlock a world of endless possibilities with ChatGPT and prompt engineering! Learn more at https://passprog.com. |
| chatgpt prompt engineering for developers certificate: Introduction to Deep Learning Sandro Skansi, 2018-02-04 This textbook presents a concise, accessible and engaging first introduction to deep learning, offering a wide range of connectionist models which represent the current state-of-the-art. The text explores the most popular algorithms and architectures in a simple and intuitive style, explaining the mathematical derivations in a step-by-step manner. The content coverage includes convolutional networks, LSTMs, Word2vec, RBMs, DBNs, neural Turing machines, memory networks and autoencoders. Numerous examples in working Python code are provided throughout the book, and the code is also supplied separately at an accompanying website. Topics and features: introduces the fundamentals of machine learning, and the mathematical and computational prerequisites for deep learning; discusses feed-forward neural networks, and explores the modifications to these which can be applied to any neural network; examines convolutional neural networks, and the recurrent connections to a feed-forward neural network; describes the notion of distributed representations, the concept of the autoencoder, and the ideas behind language processing with deep learning; presents a brief history of artificial intelligence and neural networks, and reviews interesting open research problems in deep learning and connectionism. This clearly written and lively primer on deep learning is essential reading for graduate and advanced undergraduate students of computer science, cognitive science and mathematics, as well as fields such as linguistics, logic, philosophy, and psychology. |
| chatgpt prompt engineering for developers certificate: 97 Things Every Programmer Should Know Kevlin Henney, 2010-02-05 Tap into the wisdom of experts to learn what every programmer should know, no matter what language you use. With the 97 short and extremely useful tips for programmers in this book, you'll expand your skills by adopting new approaches to old problems, learning appropriate best practices, and honing your craft through sound advice. With contributions from some of the most experienced and respected practitioners in the industry--including Michael Feathers, Pete Goodliffe, Diomidis Spinellis, Cay Horstmann, Verity Stob, and many more--this book contains practical knowledge and principles that you can apply to all kinds of projects. A few of the 97 things you should know: Code in the Language of the Domain by Dan North Write Tests for People by Gerard Meszaros Convenience Is Not an -ility by Gregor Hohpe Know Your IDE by Heinz Kabutz A Message to the Future by Linda Rising The Boy Scout Rule by Robert C. Martin (Uncle Bob) Beware the Share by Udi Dahan |
| chatgpt prompt engineering for developers certificate: Optimization for Machine Learning Suvrit Sra, Sebastian Nowozin, Stephen J. Wright, 2012 An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay between optimization and machine learning is one of the most important developments in modern computational science. Optimization formulations and methods are proving to be vital in designing algorithms to extract essential knowledge from huge volumes of data. Machine learning, however, is not simply a consumer of optimization technology but a rapidly evolving field that is itself generating new optimization ideas. This book captures the state of the art of the interaction between optimization and machine learning in a way that is accessible to researchers in both fields. Optimization approaches have enjoyed prominence in machine learning because of their wide applicability and attractive theoretical properties. The increasing complexity, size, and variety of today's machine learning models call for the reassessment of existing assumptions. This book starts the process of reassessment. It describes the resurgence in novel contexts of established frameworks such as first-order methods, stochastic approximations, convex relaxations, interior-point methods, and proximal methods. It also devotes attention to newer themes such as regularized optimization, robust optimization, gradient and subgradient methods, splitting techniques, and second-order methods. Many of these techniques draw inspiration from other fields, including operations research, theoretical computer science, and subfields of optimization. The book will enrich the ongoing cross-fertilization between the machine learning community and these other fields, and within the broader optimization community. |
| chatgpt prompt engineering for developers certificate: Data Structures and Algorithms with Python Kent D. Lee, Steve Hubbard, 2015-01-12 This textbook explains the concepts and techniques required to write programs that can handle large amounts of data efficiently. Project-oriented and classroom-tested, the book presents a number of important algorithms supported by examples that bring meaning to the problems faced by computer programmers. The idea of computational complexity is also introduced, demonstrating what can and cannot be computed efficiently so that the programmer can make informed judgements about the algorithms they use. Features: includes both introductory and advanced data structures and algorithms topics, with suggested chapter sequences for those respective courses provided in the preface; provides learning goals, review questions and programming exercises in each chapter, as well as numerous illustrative examples; offers downloadable programs and supplementary files at an associated website, with instructor materials available from the author; presents a primer on Python for those from a different language background. |
| chatgpt prompt engineering for developers certificate: Machine Learning Engineering Andriy Burkov, 2020-09-08 The most comprehensive book on the engineering aspects of building reliable AI systems. If you intend to use machine learning to solve business problems at scale, I'm delighted you got your hands on this book. -Cassie Kozyrkov, Chief Decision Scientist at Google Foundational work about the reality of building machine learning models in production. -Karolis Urbonas, Head of Machine Learning and Science at Amazon |
| chatgpt prompt engineering for developers certificate: Effective Data Storytelling Brent Dykes, 2019-12-10 Master the art and science of data storytelling—with frameworks and techniques to help you craft compelling stories with data. The ability to effectively communicate with data is no longer a luxury in today’s economy; it is a necessity. Transforming data into visual communication is only one part of the picture. It is equally important to engage your audience with a narrative—to tell a story with the numbers. Effective Data Storytelling will teach you the essential skills necessary to communicate your insights through persuasive and memorable data stories. Narratives are more powerful than raw statistics, more enduring than pretty charts. When done correctly, data stories can influence decisions and drive change. Most other books focus only on data visualization while neglecting the powerful narrative and psychological aspects of telling stories with data. Author Brent Dykes shows you how to take the three central elements of data storytelling—data, narrative, and visuals—and combine them for maximum effectiveness. Taking a comprehensive look at all the elements of data storytelling, this unique book will enable you to: Transform your insights and data visualizations into appealing, impactful data stories Learn the fundamental elements of a data story and key audience drivers Understand the differences between how the brain processes facts and narrative Structure your findings as a data narrative, using a four-step storyboarding process Incorporate the seven essential principles of better visual storytelling into your work Avoid common data storytelling mistakes by learning from historical and modern examples Effective Data Storytelling: How to Drive Change with Data, Narrative and Visuals is a must-have resource for anyone who communicates regularly with data, including business professionals, analysts, marketers, salespeople, financial managers, and educators. |
| chatgpt prompt engineering for developers certificate: Assembling the Pieces of a Systematic Review Margaret J. Foster, Sarah T. Jewell, 2017-03-03 Here is a complete guide for librarians seeking to launch or refine their systematic review services. Conducting searches for systematic reviews goes beyond expert searching and requires an understanding of the entire process of the systematic review. Just as expert searching is not fully mastered by the end of a library degree, mastering the systematic review process takes a great deal of time and practice. Attending workshops and webinars can introduce the topic, but application of the knowledge through practice is required. Running a systematic review service is complicated and requires constant updating and evaluation with new standards, more efficient methods, and improved reporting guidelines. After a brief introduction to systematic reviews, the book guides librarians in defining and marketing their services, covering topics such as when it is appropriate to ask for co-authorship and how to reach out to stakeholders. Next, it addresses developing documentation and conducting the reference interview. Standards specific to systematic reviews, including PRISMA, Institute of Medicine, and Cochrane Collaboration, are discussed. Search strategy techniques, including choosing databases, harvesting search terms, selecting filters, and searching for grey literature are detailed. Data management and critical appraisal are covered in detail. Finally, the best practices for reporting the findings of systematic reviews are highlighted. Experts with experience in both systematic reviews and librarianship, including the editors of the book, contributed to the chapters. Each step (or piece) of the review process (Planning the review, Identifying the studies, Evaluating studies, Collecting and combining data, Explaining the results, and Summarizing the review into a report), are covered with emphasis on information roles. The book is for any librarian interested in conducting reviews or assisting others with reviews. It has several applications: for training librarians new to systematic reviews, for those developing a new systematic review service, for those wanting to establish protocols for a current service, and as a reference for those conducting reviews or running a service. Participating in systematic reviews is a new frontier of librarianship, in which librarians can truly become research partners with our patrons, instead of merely providing access to resources and services. |
| chatgpt prompt engineering for developers certificate: R for Marketing Research and Analytics Chris Chapman, Elea McDonnell Feit, 2015-03-25 This book is a complete introduction to the power of R for marketing research practitioners. The text describes statistical models from a conceptual point of view with a minimal amount of mathematics, presuming only an introductory knowledge of statistics. Hands-on chapters accelerate the learning curve by asking readers to interact with R from the beginning. Core topics include the R language, basic statistics, linear modeling, and data visualization, which is presented throughout as an integral part of analysis. Later chapters cover more advanced topics yet are intended to be approachable for all analysts. These sections examine logistic regression, customer segmentation, hierarchical linear modeling, market basket analysis, structural equation modeling, and conjoint analysis in R. The text uniquely presents Bayesian models with a minimally complex approach, demonstrating and explaining Bayesian methods alongside traditional analyses for analysis of variance, linear models, and metric and choice-based conjoint analysis. With its emphasis on data visualization, model assessment, and development of statistical intuition, this book provides guidance for any analyst looking to develop or improve skills in R for marketing applications. |
| chatgpt prompt engineering for developers certificate: Learning Web Design Jennifer Robbins, 2018-05-11 Do you want to build web pages but have no prior experience? This friendly guide is the perfect place to start. You’ll begin at square one, learning how the web and web pages work, and then steadily build from there. By the end of the book, you’ll have the skills to create a simple site with multicolumn pages that adapt for mobile devices. Each chapter provides exercises to help you learn various techniques and short quizzes to make sure you understand key concepts. This thoroughly revised edition is ideal for students and professionals of all backgrounds and skill levels. It is simple and clear enough for beginners, yet thorough enough to be a useful reference for experienced developers keeping their skills up to date. Build HTML pages with text, links, images, tables, and forms Use style sheets (CSS) for colors, backgrounds, formatting text, page layout, and even simple animation effects Learn how JavaScript works and why the language is so important in web design Create and optimize web images so they’ll download as quickly as possible NEW! Use CSS Flexbox and Grid for sophisticated and flexible page layout NEW! Learn the ins and outs of Responsive Web Design to make web pages look great on all devices NEW! Become familiar with the command line, Git, and other tools in the modern web developer’s toolkit NEW! Get to know the super-powers of SVG graphics |
| chatgpt prompt engineering for developers certificate: Frank Kane's Taming Big Data with Apache Spark and Python Frank Kane, 2017-06-30 Frank Kane's hands-on Spark training course, based on his bestselling Taming Big Data with Apache Spark and Python video, now available in a book. Understand and analyze large data sets using Spark on a single system or on a cluster. About This Book Understand how Spark can be distributed across computing clusters Develop and run Spark jobs efficiently using Python A hands-on tutorial by Frank Kane with over 15 real-world examples teaching you Big Data processing with Spark Who This Book Is For If you are a data scientist or data analyst who wants to learn Big Data processing using Apache Spark and Python, this book is for you. If you have some programming experience in Python, and want to learn how to process large amounts of data using Apache Spark, Frank Kane's Taming Big Data with Apache Spark and Python will also help you. What You Will Learn Find out how you can identify Big Data problems as Spark problems Install and run Apache Spark on your computer or on a cluster Analyze large data sets across many CPUs using Spark's Resilient Distributed Datasets Implement machine learning on Spark using the MLlib library Process continuous streams of data in real time using the Spark streaming module Perform complex network analysis using Spark's GraphX library Use Amazon's Elastic MapReduce service to run your Spark jobs on a cluster In Detail Frank Kane's Taming Big Data with Apache Spark and Python is your companion to learning Apache Spark in a hands-on manner. Frank will start you off by teaching you how to set up Spark on a single system or on a cluster, and you'll soon move on to analyzing large data sets using Spark RDD, and developing and running effective Spark jobs quickly using Python. Apache Spark has emerged as the next big thing in the Big Data domain – quickly rising from an ascending technology to an established superstar in just a matter of years. Spark allows you to quickly extract actionable insights from large amounts of data, on a real-time basis, making it an essential tool in many modern businesses. Frank has packed this book with over 15 interactive, fun-filled examples relevant to the real world, and he will empower you to understand the Spark ecosystem and implement production-grade real-time Spark projects with ease. Style and approach Frank Kane's Taming Big Data with Apache Spark and Python is a hands-on tutorial with over 15 real-world examples carefully explained by Frank in a step-by-step manner. The examples vary in complexity, and you can move through them at your own pace. |
| chatgpt prompt engineering for developers certificate: Forecasting: principles and practice Rob J Hyndman, George Athanasopoulos, 2018-05-08 Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly. |
| chatgpt prompt engineering for developers certificate: Goodbye Office, Hello World! Find Freedom, Work From Anywhere and Travel the World Tim Roberts, 2022-10-19 “You don’t have to follow the path set by others. With Tim’s help, you can create the life of adventure you deserve. This book will show you the way, but you’ll have to take the first step. The world is waiting. Jeff Goins, bestselling author of The Art of Work If your goal is to explore the world while working, learning & growing, this book is essential reading. Robert Gerrish, Founder of Flying Solo, Author of 'The 1 - Minute Commute', presenter & podcaster. In the new “work from anywhere” economy, today’s workforce demands more flexibility, freedom, and financial stability. The combination of technology and the roll-on effects of the pandemic has shifted the power from the corporation to the individual. If you can’t get the outcome you desire, you need to acquire the right freelance and digital skills so you can. This book shows you how. In just a few years, Tim went from working a dead-end full-time office job to becoming location independent, all self-taught online for little money. As a result, he gained newfound freedom and zest for life. Becoming a digital nomad meant Tim could travel the world sustainably and swap the office for the shade of a palm tree, but he couldn’t have done it without assistance from the gig and sharing economies. Written in an honest, down-to-earth style, Goodbye Office, Hello World! empowers you to gain better work/lifestyle balance & integration by becoming location independent and free to travel the world. You only live once... so start living! Goodbye Office, Hello World teaches you: How to be a digital nomad with no skills by leveraging the gig economy How to find freedom as a location-independent freelancer online All the countries offering a digital nomad visa How to develop the right mindset and overcome imposter syndrome How to work remotely like a pro and travel the world How to use the sharing economy and reward points to sustain travel How to land that perfect “work from anywhere” job The role of cryptocurrency in the future of work, freelancing, and nomad life And a whole lot more! You're only one decision away from altering the course of your life for the better. Let reading this book be that decision. |
| chatgpt prompt engineering for developers certificate: Artificial Intelligence Simplified Binto George, Gail Carmichael, 2016-01-08 The book introduces key Artificial Intelligence (AI) concepts in an easy-to-read format with examples and illustrations. A complex, long, overly mathematical textbook does not always serve the purpose of conveying the basic AI concepts to most people. Someone with basic knowledge in Computer Science can have a quick overview of AI (heuristic searches, genetic algorithms, expert systems, game trees, fuzzy expert systems, natural language processing, super intelligence, etc.) with everyday examples. If you are taking a basic AI course and find the traditional AI textbooks intimidating, you may choose this as a “bridge” book, or as an introductory textbook. For students, there is a lower priced edition (ISBN 978-1944708016) of the same book. Published by CSTrends LLP. |
AI-301: ChatGPT/GPT API Prompt Engineering for Developers …
Besides gaining a basic understanding of the concepts of prompt engineering, students will also make extensive lab exercises using the OpenAI ChatGPT/GPT Python API to see how these …
The Prompt Engineering Guide - DAU
Prompt engineering is the process of designing and optimizing prompts used in natural language processing (NLP) models, such as ChatGPT, chatbots, or virtual assistants. This involves …
Prompt Engineering - web.stanford.edu
How do you as an individual scale? Stephen Henderson and Jan Jannink discussed how to remove an unwanted element from their meeting interface, which Stephen found invasive. Jan …
Prompt Engineering - rcac.purdue.edu
Effective Prompt: “Provide a concise summary of the main points in this news article about climate change.” Task: Generate a creative story starting with a given sentence.
A Prompt Pattern Catalog to Enhance Prompt Engineering …
This paper describes a catalog of prompt engineering tech- niques presented in pattern form that have been applied to solve common problems when conversing with LLMs.
Chatgpt Prompt Engineering For Developers Certificate [PDF]
on the ChatGPT prompt cheat sheet which provides a quick reference guide to the most common prompt engineering techniques This ebook is perfect for Anyone who wants to learn how to use …
Prompt Engineering for ChatGPT - iasbs.ac.ir
A prompt in the context of AI and NLP refers to the input or query given to an AI model, such as ChatGPT, to generate a response. It serves as a guide or instruction to direct the model's …
Prompt Engineering For ChatGPT: A Quick Guide To …
The objective of this article is to provide an in-depth guide on prompt engineering for ChatGPT, covering various techniques, tips, and best practices to achieve optimal results. The article is …
Mastering ChatGPT: Best Practices for Prompt Engineering
This programme empowers participants to use ChatGPT to streamline their workflow, enhance their decision-making processes, and improve their overall job performance by increasing …
Welcome to the 100 ChatGPT Prompts for Developers! Web
This is a collection of prompt examples to be used with the ChatGPT model to help you get the most out of this powerful platform. In this repository, you will find a variety of prompts that can …
Certificate in ChatGPT and Prompt Engineering for
A Certificate in ChatGPT and Prompt Engineering equips Professionals with essential skills to leverage AI effectively, enhance operational efficiency, and contribute to organizational …
Business-Ready Prompt Engineering with ChatGPT
In today’s fast-paced digital landscape, prompt engineering is becoming an essential business skill. This one-day, hands-on course is designed to empower professionals to leverage AI tools …
Mastering ChatGPT: Best Practices for Prompt Engineering
Feb 3, 2025 · Understand and apply prompt engineering strategies. output. Apply the learned concepts to real-world use cases. skills in performing information system audit engagements. …
A Prompt Pattern Catalog to Enhance Prompt Engineering …
Prompt engineering is becoming a critical skill for software developers by facilitating enhanced interactions with conversational large language models (LLMs), such as ChatGPT, Claude, …
Chatgpt Prompt Engineering For Developers Certificate [PDF]
practical techniques and real world applications of prompt engineering with a special focus on ChatGPT and its advanced iterations including GPT 4 and GPT plug ins You will learn the …
A Novel Approach for Rapid Development Based on ChatGPT …
Created a novel Prompt engineering tool that achieves a comprehensive optimization of prompts by dynamically encapsulating the original input. ⚫ Backend Service.
Chatgpt Prompt Engineering For Developers [PDF]
Within the captivating pages of Chatgpt Prompt Engineering For Developers a literary masterpiece penned by a renowned author, readers set about a transformative journey, …
Mastering ChatGPT: Best Practices for Prompt Engineering
This programme empowers participants to use ChatGPT to streamline their workflow, enhance their decision-making processes, and improve their overall job performance by increasing …
Mastering ChatGPT: Best Practices for Prompt Engineering
Mar 12, 2025 · This programme empowers participants to use ChatGPT to streamline their workflow, enhance their decision-making processes, and improve their overall job performance …
AI-301: ChatGPT/GPT API Prompt Engineering for …
Besides gaining a basic understanding of the concepts of prompt engineering, students will also make extensive lab exercises using the OpenAI ChatGPT/GPT Python API to see how these …
The Prompt Engineering Guide - DAU
Prompt engineering is the process of designing and optimizing prompts used in natural language processing (NLP) models, such as ChatGPT, chatbots, or virtual assistants. This involves …
Prompt Engineering - web.stanford.edu
How do you as an individual scale? Stephen Henderson and Jan Jannink discussed how to remove an unwanted element from their meeting interface, which Stephen found invasive. Jan …
Prompt Engineering - rcac.purdue.edu
Effective Prompt: “Provide a concise summary of the main points in this news article about climate change.” Task: Generate a creative story starting with a given sentence.
A Prompt Pattern Catalog to Enhance Prompt Engineering …
This paper describes a catalog of prompt engineering tech- niques presented in pattern form that have been applied to solve common problems when conversing with LLMs.
Chatgpt Prompt Engineering For Developers Certificate …
on the ChatGPT prompt cheat sheet which provides a quick reference guide to the most common prompt engineering techniques This ebook is perfect for Anyone who wants to learn how to …
Prompt Engineering for ChatGPT - iasbs.ac.ir
A prompt in the context of AI and NLP refers to the input or query given to an AI model, such as ChatGPT, to generate a response. It serves as a guide or instruction to direct the model's …
Prompt Engineering For ChatGPT: A Quick Guide To …
The objective of this article is to provide an in-depth guide on prompt engineering for ChatGPT, covering various techniques, tips, and best practices to achieve optimal results. The article is …
Mastering ChatGPT: Best Practices for Prompt Engineering
This programme empowers participants to use ChatGPT to streamline their workflow, enhance their decision-making processes, and improve their overall job performance by increasing …
Welcome to the 100 ChatGPT Prompts for Developers! Web …
This is a collection of prompt examples to be used with the ChatGPT model to help you get the most out of this powerful platform. In this repository, you will find a variety of prompts that can …
Certificate in ChatGPT and Prompt Engineering for
A Certificate in ChatGPT and Prompt Engineering equips Professionals with essential skills to leverage AI effectively, enhance operational efficiency, and contribute to organizational …
Business-Ready Prompt Engineering with ChatGPT
In today’s fast-paced digital landscape, prompt engineering is becoming an essential business skill. This one-day, hands-on course is designed to empower professionals to leverage AI tools …
Mastering ChatGPT: Best Practices for Prompt Engineering
Feb 3, 2025 · Understand and apply prompt engineering strategies. output. Apply the learned concepts to real-world use cases. skills in performing information system audit engagements. …
A Prompt Pattern Catalog to Enhance Prompt Engineering …
Prompt engineering is becoming a critical skill for software developers by facilitating enhanced interactions with conversational large language models (LLMs), such as ChatGPT, Claude, …
Chatgpt Prompt Engineering For Developers Certificate …
practical techniques and real world applications of prompt engineering with a special focus on ChatGPT and its advanced iterations including GPT 4 and GPT plug ins You will learn the …
A Novel Approach for Rapid Development Based on ChatGPT …
Created a novel Prompt engineering tool that achieves a comprehensive optimization of prompts by dynamically encapsulating the original input. ⚫ Backend Service.
Chatgpt Prompt Engineering For Developers [PDF]
Within the captivating pages of Chatgpt Prompt Engineering For Developers a literary masterpiece penned by a renowned author, readers set about a transformative journey, …
Mastering ChatGPT: Best Practices for Prompt Engineering
This programme empowers participants to use ChatGPT to streamline their workflow, enhance their decision-making processes, and improve their overall job performance by increasing …
Mastering ChatGPT: Best Practices for Prompt Engineering
Mar 12, 2025 · This programme empowers participants to use ChatGPT to streamline their workflow, enhance their decision-making processes, and improve their overall job performance …
