ChatGPT for Data Science and Machine Learning

Overview

This course covers an exciting journey in the application of ChatGPT in the field of Data Science and Machine Learning. Throughout this program, you will explore ChatGPT's ability as a valuable tool in data analysis, preprocessing, and machine learning model building without needing to write a single line of code!

Syllabus

• Introduction to ChatGPT
Overview of ChatGPT technology
Features and capabilities in data science
• Understanding Natural Language Processing (NLP)
Basics of NLP
Role of ChatGPT in NLP tasks
• Data Analysis with ChatGPT
Exploratory Data Analysis (EDA) using ChatGPT
Generating insights from datasets
• Data Preprocessing using ChatGPT
Handling missing data
Data transformation and normalization
Text data preprocessing techniques
• ChatGPT in Machine Learning Model Building
Defining model objectives and specifications
Model selection and tuning with ChatGPT guidance
Evaluating model performance and validation
• Automated Reporting and Insights with ChatGPT
Generating data-driven reports
Communicating findings to stakeholders
• Case Studies and Real-World Applications
Case study 1: Predictive analytics using ChatGPT
Case study 2: Sentiment analysis enhancement
Case study 3: Automating customer feedback analysis
• Challenges and Ethical Considerations
Limitations of ChatGPT in data science
Addressing biases and ensuring fairness
• Future Trends and Developments
Emerging applications of ChatGPT in data science
The role of AI in shaping future data science practices
• Course Summary and Q&A Session
Recap of key takeaways
Open discussion for questions and clarification

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Taught by

Jones Granatyr and AI Expert Academy

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Subjects

Data Science