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Generative AI for Data Analysis and Engineering with ChatGPT
Project Files and Sources
The Main Prompt Source of The Course
Prompts
Github Link
Kaggle Link
ChatGPT-4o Unleashed: Innovations in Communication and Learning
How to Use ChatGPT-4o? (5:53)
Big News: Introducing ChatGPT-4o (4:54)
Chronological Development of ChatGPT (5:21)
What Are the Capabilities of ChatGPT-4o? (4:33)
As an App: ChatGPT (3:18)
Voice Communication with ChatGPT-4o (4:50)
Instant Translation in 50+ Languages (3:03)
Interview Preparation with ChatGPT-4o (18:06)
Visual Commentary with ChatGPT-4o: Lesson 1 (4:19)
Visual Commentary with ChatGPT-4o: Lesson 2 (4:56)
Dataset Exploration and Field Knowledge
ChatGPT for Generative AI Introduction (4:21)
Accessing the Dataset (1:35)
First Task: Field Knowledge (11:12)
Using DeepSeek AI- First Task- Field Knowledge (8:26)
Using Copilot AI - First Task - Field Knowledge (7:45)
Using Gemini AI - First Task - Field Knowledge (9:54)
Continuing with Field Knowledge (5:42)
Using DeepSeek AI- Continuing with Field Knowledge (7:24)
Loading the Dataset and Understanding Variables (7:55)
Delving into the Details of Variables (5:35)
ChatGPT – Updated User Guide and Model Overview
ChatGPT Latest Updates – Free Version Interface Review (3:38)
Important Announcement (0:56)
ChatGPT Latest Updates – Paid Version Interface Review (6:52)
Chatgpt 4o Model (3:40)
Chatgpt 4o with scheduled task & 4.5 model (4:04)
ChatGPT o1 & o3 & o3 mini model (5:47)
ChatGPT – Other Models (10:35)
ChatGPT Canvas (10:00)
ChatGPT – Search & Deep Research (8:38)
Introduction to DeepSeek Tools and Features
Important Announcement (3:39)
DeepSeek Introduction - Lesson 1 (8:44)
DeepSeek Introduction - Lesson 2 (5:10)
Creating a DeepSeek Account (2:37)
Let's get to know the DeepSeek Interface (7:46)
Writing prompts with DeepSeek Lesson 1 (11:21)
Writing a Prompt with DeepSeek- DeepThink (R1) (5:23)
Writing a Prompt with DeepSeek- Search Button (1:53)
Uploading and Reading Files with DeepSeek (10:52)
Visual Analysis with DeepSeek- Graph Interpretation (6:48)
Other Visual Studies That Can Be Done with DeepSeek (5:25)
Introduction to Copilot Tools and Features
Copilot Introduction Lesson 2 (4:59)
Copilot Introduction Lesson 1 (8:01)
Creating a Copilot Account (4:35)
Copilot Interface Review (7:18)
Copilot vs. ChatGPT Comparison (12:33)
Copilot – DeepSeek Comparison (3:24)
Copilot – Story Writing (7:09)
Copilot – Think Deeper (6:44)
Reading Files with Copilot (10:51)
Visual Analysis with Copilot (8:00)
Generating Visuals with Copilot (4:28)
Introduction to Gemini Tools and Features
Gemini Interface Review (10:02)
Gemini Introduction (3:26)
Gemini Version General Reminder (1:04)
Gemini – 2.0 Flash Version (7:09)
Gemini – 2.0 Flash Thinking Experimental (8:25)
Gemini – 2.0 Flash Experimental with Apps (7:51)
Gemini – Deep Research (6:46)
Gemini – Personalization (Experimental) (4:30)
Operations on Gemini Output (6:24)
Gemini Visual Analysis (9:44)
Gemini File Reading (4:45)
Generating Images with Gemini (9:45)
Gemini Imagen 3 vs OpenAI DALL·E (6:25)
Gemini AI – Working with a Dataset Method 1 (11:02)
Gemini AI – Working with a Dataset Method 2 (Colab – Gemini Power) (13:11)
Introduction to Claude Tools and Features
Claude Interface Review (10:15)
Claude AI Introduction (7:48)
Claude 3.7 Sonnet & Normal Mode Lesson 1 (7:41)
Claude 3.7 Sonnet & Normal Mode – Lesson 2 (10:03)
Claude 3.5 Haiku & Extended Mode (7:13)
Claude 3.5 Sonnet & Claude Opus (5:52)
Processing Long Texts with Claude – Lesson 1 (10:28)
Processing Long Texts with Claude – Lesson 2 (9:13)
Visual Analysis with Claude (4:56)
Introduction to Grok Tools and Features
Grok Introduction (3:33)
Grok Interface Review (11:46)
Grok 3 Model – Lesson 1 (6:16)
Grok 3 Model – Lesson 2 (4:11)
Grok 2 Model Lesson 1 (6:10)
Grok 2 Model Lesson 2 (5:10)
Grok DeepResearch (12:12)
Grok – Deeper Research (10:05)
Grok – Think Mode (9:30)
Grok – Visual Generation (6:46)
Grok – File Reading (7:28)
Grok Visual Analysis (2:43)
Variable Analysis: Missing Data, Unique Values, and Statistics
Updating Variable Names (6:19)
Let's Perform the First Analysis (6:37)
Using DeepSeek AI Let's Perform the First Analysis (6:17)
Examining Missing Values (6:07)
Examining Unique Values (14:12)
Using DeepSeek AI- Examining Unique Values (7:26)
Using Copilot AI - Examining Unique Values (6:28)
Using Gemini AI – Examining Unique Values (9:43)
Examining Statistics of Variables Lesson 1 (15:15)
Examining Statistics of Variables Lesson 2 (13:11)
Examining Statistics of Variables Lesson 3 (9:19)
Using DeepSeek AI- Examining Statistics of Variables (13:28)
Using Copilot AI – Examining Statistics of Variables (12:17)
Using Gemini AI - Examining Statistics of Variables (8:45)
Exploratory Data Analysis (EDA) 1
Categorical Variables (Analysis with Pie Chart) Lesson 1 (10:40)
Exploratory Data Analysis (EDA) (9:59)
Categorical Variables (Analysis with Pie Chart) Lesson 2 (9:35)
Categorical Variables (Analysis with Pie Chart) Lesson 3 (6:52)
Categorical Variables (Analysis with Pie Chart) Lesson 4 (16:44)
Categorical Variables (Analysis with Pie Chart) Lesson 5 (11:19)
Exploratory Data Analysis (EDA) 2
Numerical Variables vs Target Variable Lesson 1 (6:42)
Importance of Bivariate Analysis in Data Science (7:16)
Numerical Variables vs Target Variable Lesson 2 (9:56)
Numerical Variables vs Target Variable Lesson 3 (8:24)
Numerical Variables vs Target Variable Lesson 4 (3:36)
Categoric Variables vs Target Variable Lesson 1 (3:37)
Categoric Variables vs Target Variable Lesson 2 (5:31)
Categoric Variables vs Target Variable Lesson 3 (5:21)
Categoric Variables vs Target Variable Lesson 4 (4:45)
Categoric Variables vs Target Variable Lesson 5 (5:51)
Exploratory Data Analysis (EDA) 3
Correlation Between Numerical and Categorical Variables and the Target Variable (11:42)
Correlation Between Numerical and Categorical Variables and the Target Variable (7:57)
Examining Numeric Variables Among Themselves Lesson 1 (6:12)
Examining Numeric Variables Among Themselves Lesson 2 (6:56)
Numerical Variables - Categorical Variables Lesson 1 (18:12)
Numerical Variables - Categorical Variables Lesson 2 (6:01)
Numerical Variables - Categorical Variables Lesson 3 (5:21)
Numerical Variables - Categorical Variables Lesson 4 (5:17)
Numerical Variables - Categorical Variables Lesson 5 (5:48)
Numerical Variables - Categorical Variables with Swarm Plot Lesson 1 (12:33)
Numerical Variables - Categorical Variables with Swarm Plot Lesson 2 (7:19)
Numerical Variables - Categorical Variables with Swarm Plot Lesson 3 (7:01)
Numerical Variables - Categorical Variables with Swarm Plot Lesson 4 (4:35)
Numerical Variables - Categorical Variables with Swarm Plot Lesson 5 (4:31)
Numerical Variables - Categorical Variables with Swarm Plot Lesson 6 (8:48)
Relationships between variables (Analysis with Heatmap) Lesson 1 (8:07)
Relationships between variables (Analysis with Heatmap) Lesson 2 (14:44)
Preparation for Modeling
Dropping Columns with Low Correlation (5:26)
Preparation for Modeling (5:23)
Struggling Outliers (9:50)
Visualizing Outliers Lesson 1 (6:30)
Visualizing Outliers Lesson 2 (4:33)
Visualizing Outliers Lesson 3 (3:51)
Dealing with Outliers Lesson 1 (9:24)
Dealing with Outliers Lesson 2 (13:50)
Dealing with Outliers Lesson 3 (6:02)
Dealing with Outliers Lesson 4 (6:38)
Dealing with Outliers Lesson 5 (10:03)
Determining Distributions (11:24)
Determining Distributions of Numeric Variables Lesson 1 (6:26)
Determining Distributions of Numeric Variables Lesson 2 (4:06)
Determining Distributions of Numeric Variables Lesson 3 (4:30)
Determining Distributions of Numeric Variables Lesson 4 (8:20)
Determining Distributions of Numeric Variables Lesson 5 (6:53)
Applying One Hot Encoding Method to Categorical Variables Lesson (5:19)
Applying One Hot Encoding Method to Categorical Variables Lesson 2 (2:31)
Feature Scaling with the RobustScaler Method for Machine Learning Algorithms (3:44)
Separating Data into Test and Training Set (4:00)
Machine Learning Algorithm – Logistic Regression
Logistic Regression Algorithm Lesson 1 (6:14)
Logistic Regression Algorithm Lesson 1 (11:15)
Cross Validation (8:44)
ROC Curve and Area Under Curve (AUC) Lesson 1 (6:56)
ROC Curve and Area Under Curve (AUC) Lesson 2 (5:48)
Hyperparameter Optimization (with GridSearchCV) (7:33)
Hyperparameter Tuning for Logistic Regression Model (8:28)
Machine Learning Algorithm – Decision Tree & SVM
Decision Tree Algorithm Lesson 1 (5:50)
Decision Tree Algorithm Lesson 2 (6:55)
Support Vector Machine Algorithm Lesson 1 (5:34)
Support Vector Machine Algorithm Lesson 2 (6:23)
Machine Learning Algorithm – Random Forest
Random Forest Algorithm Lesson 2 (3:37)
Random Forest Algorithm Lesson 1 (6:09)
Random Forest Algorithm Lesson 3 (5:03)
Random Forest Algorithm Lesson 4 (5:43)
Conclusion
Project Conclusion (10:35)
Suggestions and Closing (8:07)
Gemini AI – Working with a Dataset Method 2 (Colab – Gemini Power)
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