Generative AI & ChatGPT Mastery for Data Science and Python

所在平台: Udemy

课程主页: https://www.udemy.com/course/generative-ai-chatgpt-mastery-for-data-science-and-python/

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课程名称:生成式人工智能与 ChatGPT 精通:数据科学与 Python 概述: 欢迎来到《生成式人工智能与 ChatGPT 精通:数据科学与 Python》课程。本课程旨在从基础开始,帮助您掌握生成式人工智能、ChatGPT 和提示工程,以应对数据科学和 Python 相关的实际项目。随着人工智能(AI)逐渐改变我们与技术的互动方式,掌握 AI 工具已成为在数字时代保持领先的必要技能。在数据驱动的世界里,分析数据、提取有意义的见解并应用机器学习算法的能力愈加重要。本课程将引导您了解探索性数据分析(EDA)的基础知识,进而掌握高级机器学习算法,充分利用 ChatGPT-4o 的强大功能。 课程亮点: - 深入了解数据分析和机器学习管道的每一个步骤:从数据探索、可视化到建模和优化。 - 强调与 ChatGPT-4o 的结合,利用其自动化、代码生成和优化数据分析的能力,提升学习效率。 - 学习实施逻辑回归、决策树和随机森林等高级机器学习算法,并通过真实数据集进行实践,以建立和评估模型。 - 探索 AI 与机器学习结合的先进技术,推动数据分析的边界。 学习成果: 完成本课程后,您将具备: - 将原始数据转化为可操作的见解的能力。 - 自信地构建、评估和微调机器学习模型的技能。 - 利用 ChatGPT-4o 自动化数据分析、提高工作效率和加快结果输出的能力。 - 应用先进的 AI 技术解决行业级问题并做出基于数据的决策。 无论您是初学者,还是希望增强 AI 驱动分析和建模技能的爱好者,或者是想将 AI 工具整合到工作流程中的专业人士,本课程都将为您提供理论知识和实践技能的全面结合。加入我们,一起充分释放数据的潜力!

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Hi there,Welcome to "Generative AI & ChatGPT Mastery for Data Science and Python" course.Master Generative AI, ChatGPT and Prompt Engineering for Data Science and Python from scratch with hands-on projectsArtificial Intelligence (AI) is transforming the way we interact with technology, and mastering AI tools has become essential for anyone looking to stay ahead in the digital age. In today's data-driven world, the ability to analyze data, draw meaningful insights, and apply machine learning algorithms is more crucial than ever. This course is designed to guide you through every step of that journey, from the basics of Exploratory Data Analysis (EDA) to mastering advanced machine learning algorithms, all while leveraging the power of ChatGPT-4o.Data science application is an in-demand skill in many industries worldwide - including finance, transportation, education, manufacturing, human resources, and banking. Explore data science courses with Python, statistics, machine learning, and more to grow your knowledge. Get data science training if you're into research, statistics, and analytics.Machine learning describes systems that make predictions using a model trained on real-world data. For example, let's say we want to build a system that can identify if a cat is in a picture. We first assemble many pictures to train our machine learning model. During this training phase, we feed pictures into the model, along with information about whether they contain a cat. While training, the model learns patterns in the images that are the most closely associated with cats. This model can then use the patterns learned during training to predict whether the new images that it's fed contain a cat.A machine learning course teaches you the technology and concepts behind predictive text, virtual assistants, and artificial intelligence. You can develop the foundational skills you need to advance to building neural networks and creating more complex functions through the Python and R programming languages. We have more data than ever before. But data alone cannot tell us much about the world around us. We need to interpret the information and discover hidden patterns. This is where data science comes in. Data science uses algorithms to understand raw data. The main difference between data science and traditional data analysis is its focus on prediction.Python instructors at OAK Academy specialize in everything from software development to data analysis and are known for their effective, friendly instruction for students of all levels.Whether you work in machine learning or finance or are pursuing a career in web development or data science, Python is one of the most important skills you can learn. Python, python programming, python examples, python example, python hands-on, pycharm python, python pycharm, python with examples, python: learn python with real python hands-on examples, learn python, real pythonPython's simple syntax is especially suited for desktop, web, and business applications. Python's design philosophy emphasizes readability and usability. Python was developed upon the premise that there should be only one way (and preferably one obvious way) to do things, a philosophy that has resulted in a strict level of code standardization. The core programming language is quite small and the standard library is also large. In fact, Python's large library is one of its greatest benefits, providing a variety of different tools for programmers suited for many different tasks.What This Course Offers:In this course, you will gain a deep understanding of the entire data analysis and machine learning pipeline. Whether you are new to the field or looking to expand your existing knowledge, our hands-on approach will equip you with the skills you need to tackle real-world data challenges.You'll begin by diving into the fundamentals of EDA, where you'll learn how to explore, visualize, and interpret datasets. With step-by-step guidance, you'll master techniques to clean, transform, and analyze data to uncover trends, patterns, and outliers-key steps before jumping into predictive modeling.Why ChatGPT-4o?This course uniquely integrates ChatGPT-4o, the next-gen AI tool, to assist you throughout your learning journey. ChatGPT-4o will enhance your productivity by automating tasks, helping with code generation, answering queries, and offering suggestions for better analysis and model optimization. You'll see how this cutting-edge AI transforms data analysis workflows and unlocks new levels of efficiency and creativity.Mastering Machine Learning:Once your foundation in EDA is solid, the course will guide you through advanced machine learning algorithms such as Logistic Regression, Decision Trees, Random Forest, and more. You'll learn not only how these algorithms work but also how to implement and optimize them using real-world datasets. By the end of the course, you'll be proficient in selecting the right models, fine-tuning hyperparameters, and evaluating model performance with confidence.What You'll Learn:Exploratory Data Analysis (EDA): Master the techniques for analyzing and visualizing data, detecting trends, and preparing data for modeling.Machine Learning Algorithms: Implement algorithms like Logistic Regression, Decision Trees, and Random Forest, and understand when and how to use them.ChatGPT-4o Integration: Leverage the AI capabilities of ChatGPT-4o to automate workflows, generate code, and improve data insights.Real-World Applications: Apply the knowledge gained to solve complex problems and make data-driven decisions in industries such as finance, healthcare, and technology.Next-Gen AI Techniques: Explore advanced techniques that combine AI with machine learning, pushing the boundaries of data analysis.Why This Course Stands Out:Unlike traditional data science courses, this course blends theory with practice. You won't just learn how to perform data analysis or build machine learning models-you'll also apply these skills in real-world scenarios with guidance from ChatGPT-4o. The hands-on projects ensure that by the end of the course, you can confidently take on any data challenge in your professional career.In this course, you will Learn:What is Artificial Intelligence?Artificial Narrow Intelligence (ANI)Artificial General Intelligence (AGI)Artificial Super Intelligence (ASI)Subsets of Artificial Intelligence - Machine LearningSubsets of Artificial Intelligence - Deep LearningMachine Learning vs. Deep LearningMachine Learning Study with a Real ExampleLarge Language Models(LLM)Natural Language Processing(NLP)A Warning Before Switching to ChatGPTRevolutionary of the Era: OpenAIThe Revolution of the Age: Creating a ChatGPT AccountLet's Get to Know the ChatGPT InterfaceChatGPT: Differences Between VersionsDifferences in the ChatGPT-4 InterfaceChatGPT's EndpointsChatGPT's Secret to More Accurate Answers: PromptPrompt Engineering PowerSummary of Prompt Engineering FundamentalsPrompt Engineering: Sample PromptsBest Questions in Prompt EngineeringSummary of the Best Questions in Prompt EngineeringReinforcing the topic through a scenarioDrawing a Roadmap to the PromptDirected Writing RequestClear Explanation MethodExample-Based LearningRGC(Role, Goals, Context)Constrained ResponsesAdding Visual AppealPrompt UpdatesChatGPT-Google ExtensionEmail WritingSummarizing YouTube VideosTalk to ChatGPTQuick Access to ChatGPTDive Into WebsitesGet Prompt AssistanceUsing the ChatGPT APIFile ReadingVisual ReadingVisual Generation (DALL-E Introduction)Enhancing Images with DALL-EImproving Visuals Through Ready-Made PromptsCombining ImagesA Helper Site for Visual PromptsGPTsCreate Your Own GPTUseful GPTsBig News: Introducing ChatGPT-4oHow to Use ChatGPT-4o?Chronological Development of ChatGPTWhat Are the Capabilities of ChatGPT-4o?As an App: ChatGPTVoice Communication with ChatGPT-4oInstant Translation in 50+ LanguagesInterview Preparation with ChatGPT-4oVisual Commentary with ChatGPT-4oGetting to know the dataset using ChatGPTGetting started with Exploratory Data Analysis(EDA) using ChatGPTPerform Univariate Analysis using ChatGPTPerform Bivariate Analysis using ChatGPTPerform Multivariate Analysis using ChatGPTPerform Correlation Analysis using ChatGPTPrepare data for machine learning model using ChatGPTCreate a machine learning model using the Linear Regression algorithm with ChatGPTDevelop machine learning model using ChatGPTPerform Feature Engineering using ChatGPTPerforming Hyperparameter Optimization using ChatGPT2.1 Loading Dataset using ChatGPTPerform initial analysis on Dataset using ChatGPTPerforming the first operation on the Dataset using ChatGPTTackling Missing values ​​using ChatGPTPerforming Bivariate analysis with CatPLot using ChatGPTPerforming Bivariate analysis with KdePLot using ChatGPTExamining the correlation of variables using ChatGPTPerform a get_dummies operation using ChatGPTPrepare for Logistic Regression modeling using ChatGPTCreate a Logistic Regression model using ChatGPTExamining evaluation metrics on the Logistic Regression model using ChatGPTPerform a GridSearchCv operation using ChatGPTModel reconstruction with best parameters using ChatGPTSummaryBeginners who want a structured, comprehensive introduction to data analysis and machine learning.Data enthusiasts looking to enhance their AI-driven analysis and modeling skills.Professionals who want to integrate AI tools like ChatGPT-4o into their data workflows.Anyone interested in mastering the art of data analysis, machine learning, and next-generation AI techniques.What You'll Gain:By the end of this course, you will have a robust toolkit that enables you to:Transform raw data into actionable insights with EDA.Build, evaluate, and fine-tune machine learning models with confidence.Use ChatGPT-4o to streamline data analysis, automate repetitive tasks, and generate faster results.Apply advanced AI techniques to tackle industry-level problems and make data-driven decisions.This course is your gateway to mastering data analysis, machine learning, and AI, and it's designed to provide you with both the theoretical knowledge and practical skills needed to succeed in today's data-centric world.Join us on this complete journey and unlock the full potential of data with ChatGPT-4o and advanced machine learning algorithms. Let's get started!Video and Audio Production QualityAll our videos are created/produced as high-quality video and audio to provide you the best learning experience.You will be,Seeing clearlyHearing clearlyMoving through the course without distractionsYou'll also get:Lifetime Access to The CourseFast & Friendly Support in the Q & A sectionUdemy Certificate of Completion Ready for DownloadDive in now!We offer full support, answering any questions.See you in the "Generative AI & ChatGPT Mastery for Data Science and Python" course.Master Generative AI, ChatGPT and Prompt Engineering for Data Science and Python from scratch with hands-on projects

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