ChatGPT for Python Data Science and Machine Learning

Overview

Master Data Analysis, Regression, Classification, Clustering and Pandas Coding with ChatGPT! A Project-based Course.

What you'll learn:

Use ChatGPT for real-life Data Science and Machine Learning ProjectsLet ChatGPT write do the Coding work (Python, Pandas, scikit-learn etc.)Use ChatGPT to select the most suitable Machine Learning ModelUse ChatGPT to analyse and interpret the outcomes of Machine Learning & Statistical ModelsPerform an Explanatory Data Analysis with ChatGPT and PythonUse ChatGPT for Data Manipulation, Aggregation, advanced Pandas Coding & moreUse ChatGPT to fit and evaluate Regression and Classification ModelsUse ChatGPT for Multiple Regression Analysis and Hypothesis TestingUse ChatGPT for Error Handling and TroubleshootingMaster Clustering and Unsupervised Learning with ChatGPT **Updated:

Now including the latest models GPT-4o and GPT-4o mini**Welcome to the first Data Science and Machine Learning course with ChatGPT. Learn how to use ChatGPT to master complex Data Science and Machine Learning real-life projects in no time!

Why is this a game-changing course?Real-world Data Science and Machine Learning projects require a solid background in advanced statistics and Data Analytics. And it would be best if you were a proficient Python Coder.

Do you want to learn how to master complex Data Science projects without the need to study and master all the required basics (which takes dozens if not hundreds of hours)? Then this is the perfect course for you!

What you can do at the end of the course:

At the end of this course, you will know and understand all strategies and techniques to master complex Data Science and Machine Learning projects with the help of ChatGPT! And you don´t have to be a Data Science or Python Coding expert!

Use ChatGPT as your assistant and let ChatGPT do the hard work for you! Use ChatGPT forthe theoretical part Python codingevaluating and interpreting coding and ML resultsThis course teaches prompting strategies and techniques and provides dozens of ChatGPT sample prompts toload, initially inspect, and understand unknown datasets clean and process raw datasets with Pandasmanipulate, aggregate, and visualize datasets with Pandas and matplotlibperform an extensive Explanatory Data Analysis (EDA) for complex datasetsuse advanced statistics, multiple regression analysis, and hypothesis testing to gain further insightsselect the most suitable Machine Learning Model for your prediction tasks (Model Selection)evaluate and interpret the performance of your Machine Learning models (Performance Evaluation)optimize your models via handling Class Imbalance, Hyperparameter Tuning & more.evaluate and interpret the results and findings of your predictions to solve real-world business problemsmaster regression, classification, and unsupervised learning/clustering projectsWe´ll cover prompting strategies and tactics for GPT-3.5 / GPT-4o mini (free) and GPT-4 / GPT-4o (paid subscription).

Know the differences and master both!The course is organized into Do-it-yourself projects with detailed project assignments and supporting materials. At the end, you will find a video sample solution.

All solutions and sample prompts are available for simple download or copy/paste! Who is this Course for?Data Science Beginners who have no time to learn everything from scratchSkilled Data Scientists seeking to outsource the most time-consuming parts of their work to save time Are you ready to be at the forefront of AI in Data Science?

Enroll now and start transforming your professional landscape with AI and ChatGPT!

Syllabus

• Introduction to AI and GPT Models
Overview of AI in data science and machine learning
Introduction to OpenAI's GPT models
Understanding the evolution from GPT-3 to GPT-4o
• Setting Up the Environment
Installing Python and essential libraries
Setting up a Jupyter Notebook for data science
Accessing OpenAI API with API keys
• Basics of ChatGPT
Understanding GPT-4o architecture
Exploring GPT-4o mini: Use cases and limitations
Tokenization and language modeling fundamentals
• Using ChatGPT for Data Science
Data preprocessing with GPT
Text analysis and NLP tasks using GPT
Generating insights from datasets using natural language generation
• Applications in Machine Learning
Feature engineering with ChatGPT
Using ChatGPT for data augmentation
Automating data labeling and annotation
• GPT-Enhanced Model Building
Experiment design with ChatGPT
Model interpretation and debugging using natural language explanations
Fine-tuning machine learning models with GPT assistance
• Advanced Topics
Integrating GPT-4o models within data pipelines
Exploring reinforcement learning with GPT models
Ethical considerations and limitations of using GPT in data science
• Practical Projects
Building a conversational chatbot for data querying
Analyzing large datasets using GPT for exploratory data analysis
Creating a GPT-driven automated reporting tool
• Conclusion and Future Directions
Future trends in AI and language models
Continuing education and resources for AI advancements
• Course Review and Q&A
Recap of key concepts
Open session for questions and troubleshooting

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Taught by

Alexander Hagmann

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Subjects

Data Science