Welcome to the world of ChatGPT – an advanced language model based on Artificial Intelligence (AI), designed to assist and enhance your learning journey in the fascinating field of AI. Developed by OpenAI, ChatGPT leverages the power of the GPT-3.5/4 architecture, making it a versatile and intelligent language model capable of generating human-like responses to a wide range of prompts.
How can ChatGPT Help You Learn AI?
ChatGPT serves as an invaluable learning companion for anyone interested in delving into the world of Artificial Intelligence. By utilizing the provided prompts, you can embark on a journey of exploration, discovery, and understanding of AI concepts, technologies, and applications. The pre-existing AI prompts have been carefully crafted to guide your learning experience and provide you with comprehensive insights into key AI topics.
Ready-to-Use AI Prompts
ChatGPT offers a collection of ready-to-use AI prompts that serve as valuable starting points for your learning endeavors. These prompts encompass a wide spectrum of AI topics, ranging from basic concepts like machine learning and neural networks to advanced subjects such as AI ethics, explainable AI, and AI in business. Simply engage with ChatGPT using these prompts, and you will receive concise and informative responses to expand your knowledge.
Generating Information and Guidelines
In addition to the predefined prompts, ChatGPT can also generate custom information and guidelines for your specific learning needs. You can request ChatGPT to explain specific AI terminologies, provide examples of AI applications in real-world scenarios, or offer guidance on best practices for AI development. The versatility of ChatGPT ensures that you receive tailored and relevant information to accelerate your learning process.
Embrace Interactive Learning
Through interactive conversations with ChatGPT, you can ask questions, seek clarification, and explore AI concepts in an engaging and dynamic manner. This interactive learning experience enables you to grasp complex concepts intuitively, and ChatGPT is here to support your quest for AI knowledge every step of the way.
Leverage ChatGPT’s Knowledge Cutoff
It is essential to note that ChatGPT’s responses are based on a knowledge cutoff up to September 2021. While it holds a wealth of information within that timeframe, please be aware that it may not be aware of more recent developments in the AI field.
Begin Your AI Learning Journey with ChatGPT
Whether you are a student, professional, or AI enthusiast, ChatGPT is your gateway to exploring the wonders of Artificial Intelligence. From fundamental concepts to cutting-edge trends, ChatGPT’s AI prompts are your key to unlocking a deeper understanding of AI technologies, applications, and implications. So, let’s embark on this educational adventure together and unleash the potential of AI learning with ChatGPT!
The bundle includes:
Introduction to AI
ChatGPT for Machine Learning Algorithms
ChatGPT for Deep Learning Algorithms
ChatGPT Data Science – Master Edition
ChatGPT Python
ChatGPT for Python Libraries – Gold Bundle
Who is this guide for?
This guide is for anyone who seeks to learn and explore Artificial Intelligence (AI) with the assistance of ChatGPT. Whether you are a student, a professional in the field, an AI enthusiast, or simply curious about the fascinating world of AI, ChatGPT is here to support your learning journey. The guide is designed to cater to learners of all levels, offering ready-to-use AI prompts and generating custom information to provide comprehensive insights into various AI concepts, technologies, and applications. So, if you are eager to dive into the world of AI and engage in interactive conversations to enhance your understanding, this guide is the perfect companion for you. Let’s embark on this educational adventure together and discover the potential of AI learning with ChatGPT!
Introduction to AI
AI Applications
AI Ethics
AI Technologies
AI in Business
AI Research and Trends
AI and Society
AI in Entertainment
AI and Sustainability
AI and Future Predictions
AI Explained
ChatGPT for Machine Learning Algorithms
Supervised Learning Algorithms
Unsupervised Learning Algorithms
Deep Learning Algorithms
Natural Language Processing (NLP) Algorithms
Reinforcement Learning Algorithms
Ensemble Learning
Recommendation Systems
Time Series Analysis
Machine Learning Model Evaluation and Optimization
Explainable AI (XAI)
ChatGPT for Deep Learning Algorithms
Neural Networks
Convolutional Neural Networks (CNNs)
Recurrent Neural Networks (RNNs)
Transformers
Generative Adversarial Networks (GANs)
Autoencoders
Optimization Algorithms
Regularization Techniques
Deep Reinforcement Learning
Quantum Deep Learning
ChatGPT Data Science – Master Edition
Data Analyst R
Introduction to R
Introduction to the Tidyverse
Data Manipulation with dplyr
Joining Data with dplyr
Introduction to Statistics in R
…
Data Scientist R
Data Communication Concept
Cleaning Data in R
Working with Dates and Times in R
Introduction to Regression in R
Supervised Learning in R: Classification
Supervised Learning in R: Regression
Unsupervised Learning
…
Data Analyst Python
Data Manipulation with Pandas
Joining Data with Pandas
Introduction to Statistics in Python
Importing & Cleaning Data with Python
Exploratory Data Analysis in Python
Sampling in Python
…
Data Scientist Python
Python Programming for Data Science
Writing Functions in Python
Python Libraries for Data Science
Machine Learning Algorithms in Python
Supervised Learning with scikit-learn
Machine Learning with Tree-Based Models in Python
Python for Data Science in the Cloud
…
Quantitative Analyst R
Manipulating Time Series with xts and zoo in R
Arima models in R
Portfolio analysis and optimization in R
Risk Management and Simulation with R
Visualizing Time Series Data in R
Bond Valuation and Analysis in R
Financial Trading in R
…
Data Engineer Python
Data Ingestion
Data Processing
Data Modeling
Data Pipelines
Data Quality and Governance
Data Visualization and Reporting
Performance Optimization and Scalability
…
Data Analyst PowerBI
Data visualization in Power BI
DAX (Data Analysis Expressions) in Microsoft Power BI
Power BI Desktop features
Power BI Query Editor
Power BI data sources
Power BI dashboards and reports
Power BI integration and automation
…
Data Analyst Tableau
10 categories
Statistician
10 categories
ML Scientist
10 categories
and much more
ChatGPT Python
Exploring the Basics
Data Structures and Manipulation
Reading and Writing Data
Data Cleaning and Preprocessing
Exploratory Data Analysis (EDA)
Statistical Analysis
Machine Learning for Data Analysis
Time Series Analysis
Text Analysis
Advanced Topics
Exercises
Python Fundamentals
Control Flow
Functions
Data Structures
File Handling
String Manipulation
Error Handling
Object-Oriented Programming (OOP)
Modules and Libraries
Advanced Concepts
ChatGPT for Python Libraries – Gold Bundle
Pandas
Pandas Basics
DataFrame Operations
Data Cleaning with Pandas
Data Visualization with Pandas
Pandas and Data Analysis
Time Series Analysis with Pandas
Data Transformation with Pandas
Grouping and Aggregation
Pandas Best Practices
Pandas Case Studies and Projects
NumPy
Introduction and Basics
Array Manipulation
Mathematical Operations
Array Broadcasting
Array Indexing and Selection
Performance Optimization
Data Analysis and Statistics
Linear Algebra
File I/O and Integration
Advanced NumPy Features
Keras
Introduction to Keras
Keras Tutorials
Model Building with Keras
Keras Layers and Architectures
Transfer Learning with Keras
Hyperparameter Tuning in Keras
Keras Callbacks
Keras and TensorFlow Integration
Keras in Real-World Projects
Keras Updates and News
TensorFlow
Introduction to TensorFlow
Tutorials and How-tos
Tips and Tricks
Model Showcase
Community Spotlights
Performance Optimization
Error Handling and Debugging
Integration with Other Libraries
Data Visualization with TensorFlow
Scrapy
Getting Started
Spider Development
XPath and CSS Selectors
Middleware and Pipelines
Crawling Best Practices
Using Proxies and User Agents
Scrapy Extensions and Customizations
Real-World Use Cases
SciPy
Introduction to SciPy
Key Modules and Functions
Use Cases and Applications
Tutorials and How-tos
Performance and Optimization
Data Visualization with SciPy
Comparison with Other Libraries
Tips and Tricks
PyTorch
Tutorials for Beginners
Advanced Tutorials
Model Building and Training
PyTorch and Computer Vision
Natural Language Processing (NLP) with PyTorch
PyTorch and Reinforcement Learning
Deployment and Production
PyTorch Ecosystem
PyTorch and Research
LightGBM
Introduction and Basics
Installation and Setup
Feature Engineering
Hyperparameter Tuning
Model Training and Evaluation
Advanced Features
Model Interpretability
Integration with Other Libraries
Real-World Applications
Theano
Introduction to Theano
Theano Tutorials
Advanced Theano Techniques
Comparisons with Other Libraries
Optimization and Performance
Real-world Use Cases
Debugging and Troubleshooting
Theano Tips and Best Practices
Scikit Learn
Introduction to Scikit Learn
Key Features and Functions
Tutorials and How-To Guides
Data Preprocessing with Scikit Learn
Model Evaluation and Metrics
Ensemble Methods
Hyperparameter Tuning
Handling Imbalanced Data
Working with Text Data
Deploying Machine Learning Models
Introducing ChatGPT for Data Engineering
Data engineering is the backbone of modern data-driven organizations. It involves the processes of collecting, transforming, and delivering data to enable valuable insights, decision-making, and machine learning. Data engineers play a pivotal role in designing and maintaining data pipelines, ensuring data quality, and facilitating seamless data access for analysts and data scientists.
Our goal with ChatGPT for Data Engineering is to provide a comprehensive resource that empowers you to:
Learn Key Concepts: Gain a solid understanding of fundamental data engineering concepts, such as ETL (Extract, Transform, Load), data warehousing, data quality, and real-time data processing.
Master Best Practices: Access best practices and industry insights to build efficient and scalable data pipelines, implement robust data governance, and enhance data security.
Navigate Tools and Technologies: Explore a variety of data engineering tools and technologies, including cloud platforms, big data frameworks, and data integration solutions, with guidance on selecting the right tools for your projects.
Achieve Compliance: Understand the importance of data compliance and learn how to align your data engineering efforts with regulations like GDPR, HIPAA, and more.
Enhance Career Skills: Discover tips and strategies for career development in the data engineering field, including skill enhancement, networking, and staying up-to-date with industry trends.
In this guide, you will find a range of prompts that serve different purposes. Some prompts are ready-made, providing immediate answers to common questions, while others generate detailed information and guidelines for more in-depth learning. These prompts are designed to foster a dynamic and interactive learning experience, allowing you to explore various aspects of data engineering at your own pace.
Whether you’re seeking specific answers or looking to deepen your knowledge, ChatGPT for Data Engineering is here to assist you on your journey. Let’s embark on this learning adventure together, unlocking the vast potential of data engineering and paving the way for data-driven success.
What’s in the guide?
Foundations
Python
Java
Databricks
Apache Spark
Kafka
Kubernetes
Docker
SQL
NoSQL
MongoDB
Software Engineering
DevOps
AWS Machine Learning
Google Cloud Machine Learning
Microsoft Azure Machine Learning
Total prompts:5000+
How does it work?
Pay what you want (or enter $0 if the free version)
Go to the Notion page containing the guide and bookmark it
Or choose to duplicate the page into your own Notion workspace to save it
You’ll be able to navigate through the directory using the different categories and tags.
Bonus: Add your own resources to the guide and keep building!
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