Prompt Engineering for Data Analysis Python, Pandas, ChatGPT

Unlock the potential of data analysis with this focused course on prompt engineering and Python, designed for those looking to master the integration of ChatGPT with data tools like Pandas. Whether you're a beginner or have some coding experience, this course takes you step-by-step through setting up your environment, learning Python fundamentals, and diving into practical data analysis using prompt engineering techniques. From importing data to building insights and creating visualizations, this course covers everything you need to turn raw data into actionable insights.

What You'll Learn:Essentials of Prompt Engineering with ChatGPT: Begin with the basics of prompt engineering and learn how to communicate effectively with ChatGPT, enhancing its usefulness for data-related tasks. Python Setup & Jupyter Notebook Basics: Set up your Python environment with Anaconda, Jupyter Notebook, and Google Colab, ensuring you have the tools you need to work efficiently across platforms. Pandas for Data Analysis: Dive into essential Pandas skills, from working with Series and DataFrames to advanced data manipulation with functions like GroupBy.

Learn prompt engineering strategies to streamline tasks and increase analysis efficiency. Data Visualization and Data Management: Explore data visualization techniques and discover how to import, export, and handle multiple data files. These skills empower you to present findings effectively and manage complex data projects.

Real-World Projects: Apply what you've learned to hands-on projects, including e-commerce transaction analysis, salary dataset exploration, movie success factor analysis, and stock performance. Each project is designed to give you experience with real-world data and enhance your problem-solving skills. Build GUI Apps in Python: Move beyond data analysis to learn how to create GUI applications, adding a user-friendly interface to your data solutions and making your work accessible to non-technical users.