Course Outline

Introduction to ChatGPT for Data Science and Analytics

  • What is ChatGPT and how does it work?
  • Overview of ChatGPT's role in data science and analytics

Data Exploration with ChatGPT

  • Leveraging ChatGPT for exploratory data analysis
  • Asking natural language questions to ChatGPT for data insights
  • Assisting in data cleaning and preprocessing with ChatGPT

Generating Insights with ChatGPT

  • Using ChatGPT to uncover patterns and trends in data
  • Leveraging ChatGPT for feature engineering and selection
  • Assisting in hypothesis generation and testing with ChatGPT

ChatGPT for Predictive Modeling

  • Incorporating ChatGPT in predictive modeling workflows
  • Generating predictions and forecasts with ChatGPT
  • Assisting in model selection and evaluation using ChatGPT

ChatGPT for Natural Language Processing (NLP)

  • Utilizing ChatGPT for text analysis and sentiment analysis
  • Extracting meaningful information from unstructured text data
  • Incorporating ChatGPT in NLP pipelines and applications

Best Practices for ChatGPT in Data Science and Analytics

  • Fine-tuning ChatGPT for specific data science tasks
  • Addressing bias and fairness considerations in AI-assisted analytics
  • Monitoring and evaluating ChatGPT performance and results

Ethical Use of ChatGPT in Data Science and Analytics

  • Ensuring responsible and transparent use of AI in data science
  • Mitigating risks and ethical challenges associated with ChatGPT
  • Understanding ethical considerations in deploying AI models powered by ChatGPT

Future Trends and Developments

  • Exploring advancements in ChatGPT and data science
  • Implications of AI in the future of data analytics
  • Opportunities for innovation and growth with ChatGPT in data science and analytics

Summary and Next Steps


  • Basic computer experience
  • Familiarity with data science concepts and tools


  • Data scientists
  • Data analysts
  • Business analysts
  • Data engineers
  14 Hours


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