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Generative Ai & Chatgpt Mastery For Data Science And Python
Published 12/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 9.12 GB | Duration: 24h 6m
Master Generative AI, ChatGPT and Prompt Engineering for Data Science and Python from scratch with hands-on projects
What you'll learn
What is Artificial Intelligence?
Artificial Narrow Intelligence (ANI)
Artificial General Intelligence (AGI)
Artificial Super Intelligence (ASI)
Subsets of Artificial Intelligence - Machine Learning
Subsets of Artificial Intelligence - Deep Learning
Machine Learning Study with a Real Example
Large Language Models(LLM)
Natural Language Processing(NLP)
A Warning Before Switching to ChatGPT
Revolutionary of the Era: OpenAI
Let's Get to Know the ChatGPT Interface
Differences in the ChatGPT-4 Interface
ChatGPT's Endpoints
Prompt Prompt Engineering Power
Summary of Prompt Engineering Fundamentals
Prompt Engineering: Sample Prompts
Best Questions in Prompt Engineering
Summary of the Best Questions in Prompt Engineering
Reinforcing the topic through a scenario
Drawing a Roadmap to the Prompt
Directed Writing Request
Clear Explanation Method
Example-Based Learning
RGC(Role, Goals, Context)
Constrained Responses
Adding Visual Appeal
Prompt Updates
ChatGPT-Google Extension
Email Writing
Summarizing YouTube Videos
Talk to ChatGPT
Quick Access to ChatGPT
Dive Into Websites
Get Prompt Assistance
Using the ChatGPT API
File Reading
Visual Reading
Visual Generation (DALL-E Introduction)
Enhancing Images with DALL-E
Improving Visuals Through Ready-Made Prompts
Combining Images
A Helper Site for Visual Prompts
GPTs
Create Your Own GPT
Useful GPTs
Big News: Introducing ChatGPT-4o
How to Use ChatGPT-4o?
Chronological Development of ChatGPT
What Are the Capabilities of ChatGPT-4o?
Voice Communication with ChatGPT-4o
Instant Translation in 50+ Languages
Interview Preparation with ChatGPT-4o
Visual Commentary with ChatGPT-4o
Data analysis is the process of studying or manipulating a dataset to gain some sort of insight
Big News: Introducing ChatGPT-4o
How to Use ChatGPT-4o?
Chronological Development of ChatGPT
What Are the Capabilities of ChatGPT-4o?
As an App: ChatGPT
Voice Communication with ChatGPT-4o
Instant Translation in 50+ Languages
Interview Preparation with ChatGPT-4o
Visual Commentary with ChatGPT-4o
ChatGPT for Generative AI Introduction
Accessing the Dataset
First Task: Field Knowledge
Loading the Dataset and Understanding Variables
Let's Perform the First Analysis
Examining Missing Values
Examining Unique Values
Categorical Variables (Analysis with Pie Chart)
Exploratory Data Analysis (EDA)
Categoric Variables vs Target Variable
Correlation Between Numerical and Categorical Variables and the Target Variable
Relationships between variables (Analysis with Heatmap)
Numerical Variables - Categorical Variables with Swarm Plot
Dropping Columns with Low Correlation
Visualizing Outliers
Determining Distributions
Applying One Hot Encoding Method to Categorical Variables
Feature Scaling with the RobustScaler Method for Machine Learning Algorithms
Feature Scaling with the RobustScaler Method for Machine Learning Algorithms
Logistic Regression Algorithm
Cross Validation
ROC Curve and Area Under Curve (AUC)
ROC Curve and Area Under Curve (AUC)
Hyperparameter Tuning for Logistic Regression Model
Decision Tree Algorithm
Support Vector Machine Algorithm
Random Forest Algorithm
Generative AI is artificial intelligence (AI) that can create original content in response to a user's prompt or request
Getting to know the dataset using ChatGPT
Getting started with Exploratory Data Analysis(EDA) using ChatGPT
Perform Multivariate Analysis using ChatGPT
Prepare data for machine learning model using ChatGPT
Create a machine learning model using the Linear Regression algorithm with ChatGPT
Develop machine learning model using ChatGPT
Perform Feature Engineering using ChatGPT
Performing Hyperparameter Optimization using ChatGPT
Loading Dataset using ChatGPT
Perform initial analysis on Dataset using ChatGPT
Performing the first operation on the Dataset using ChatGPT
Tackling Missing values using ChatGPT
Performing Bivariate analysis with CatPLot using ChatGPT
Performing Bivariate analysis with KdePLot using ChatGPT
Examining the correlation of variables using ChatGPT
Perform a get_dummies operation using ChatGPT
Prepare for Logistic Regression modeling using ChatGPT
Create a Logistic Regression model using ChatGPT
Examining evaluation metrics on the Logistic Regression model using ChatGPT
Perform a GridSearchCv operation using ChatGPT
Model reconstruction with best parameters using ChatGPT
Requirements
A working computer (Windows, Mac, or Linux)
Motivation to learn the the second largest number of job postings relative AI among all others
Desire to learn AI & ChatGPT
Curiosity for Artificial Intelligence and Data Science
Nothing else! It's just you, your computer and your ambition to get started today
Basic python knowledge
Description
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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