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Generative AI & ChatGPT Mastery for Data Science and Python | Udemy [Update 12/2024]
English | Size: 10.34 GB
Genre: eLearning[/center]

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

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 projects

Artificial 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 python

Python'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 Learning

Subsets of Artificial Intelligence - Deep Learning

Machine Learning vs. 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

The Revolution of the Age: Creating a ChatGPT Account

Let's Get to Know the ChatGPT Interface

ChatGPT: Differences Between Versions

Differences in the ChatGPT-4 Interface

ChatGPT's Endpoints

ChatGPT's Secret to More Accurate Answers: 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?

As an App: ChatGPT

Voice Communication with ChatGPT-4o

Instant Translation in 50+ Languages

Interview Preparation with ChatGPT-4o

Visual Commentary with ChatGPT-4o

Getting to know the dataset using ChatGPT

Getting started with Exploratory Data Analysis(EDA) using ChatGPT

Perform Univariate Analysis using ChatGPT

Perform Bivariate Analysis using ChatGPT

Perform Multivariate Analysis using ChatGPT

Perform Correlation 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

2.1 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

Summary

Beginners 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 Quality

All our videos are created/produced as high-quality video and audio to provide you the best learning experience.

You will be,

Seeing clearly

Hearing clearly

Moving through the course without distractions

You'll also get:

Lifetime Access to The Course

Fast & Friendly Support in the Q&A section

Udemy Certificate of Completion Ready for download скачать

Dive 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

Who this course is for:
Anyone who wants to start learning AI & ChatGPT
Anyone who needs a complete guide on how to start and continue their career with AI & Prompt Engineering
And also, who want to learn how to develop Prompt Engineering
Data Analyst who want to apply generative AI tools to automate repetitive tasks, streamline data workflows, and generate insights.
Data Engineer who wants to optimize data pipelines and automate data-related tasks.
AI and Machine Learning Enthusiasts who want to deepen their understanding of how generative AI models, like ChatGPT, can be applied to real-world data tasks.
Business Analysts who wants to understand how generative AI can assist in generating business insights from raw data
Students or Beginners in Data Science who want to get familiar with cutting-edge AI tools and apply them to basic data analysis, engineering, or project automation.

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