Join our interactive course, "Complete Guide to ChatGPT & Copilot for Python & R Projects", designed to give you hands-on experience in solving real data science problems using AI, Copilot, and ChatGPT.

With Udemy's 30-day money-back guarantee in place, there's no need to worry if the class doesn't meet your expectations.

The course is taught both in Python and R with RStudio. A complete installation guide on how to install and configure Python and R, was added in April 2024. It also explains how to connect RStudio to Python and use it as Python's IDE.

Each lesson in this course stands alone, focusing on a different data science challenge.

You'll learn how to apply AI tools like Copilot and ChatGPT to navigate through these challenges efficiently.

Incorporating AI tools like Copilot and ChatGPT into your data science workflow can significantly enhance your speed and efficiency, often doubling (X2) or even increasing productivity tenfold (X10), depending on the task at hand.

Here's what we'll cover, using practical, project-based learning:

• Data Clean-up and Tidy: Learn how to organize your data neatly, making it ready for analysis. This is a key step in data science to ensure your data is accurate and easy to work with. Using Pandas with Python and dplyr with R.

• Load Files of Different Formats: Discover how to bring in data from different kinds of files. This skill is important in data science because it lets you work with all sorts of data in tools like Copilot and ChatGPT.

• Data Visualization with Graphs: Find out how to use graphs to show your data in a clear and interesting way. Graphs help you see patterns and important points, which is a big part of data science.

• Data Visualization with Tables: Learn how tables can help you display data simply and effectively, making it easier to compare and understand, a common task in data science.

• Fetch API Data: Gain skills in collecting live data from APIs. This means you can use fresh, real-world data in your data science projects with Copilot and ChatGPT. Both Python and R have great libraries to fetch API data.

• Web Scrapping: Learn how to scrape data that comes in various formats like text and HTML tables. This ensures you can capture all the relevant information from a website. Python and R will do these tasks differently depending on webpage.

• Connect and Fetch from SQL: Learn how to get data from SQL databases, which is essential for dealing with organized data in many data science projects.

• Data Table Manipulations and Joins: Get into more advanced ways to work with tables, like changing data and putting tables together to get more insights, a useful technique in data science.

• Regression Analysis: Understand the basics of regression analysis, which helps you see how things are connected and predict future trends, a key method in data science.

• Text Mining: Explore how to pull out useful information from text, an important skill in data science, especially when working with tools like ChatGPT to analyze large amounts of text data.

• Machine Learning: Start building machine learning models, which let you find patterns and make predictions from data, a core part of data science. Python is the clear winner but R catching up!

• Portfolio Return Analytics: Dive into analyzing investment returns, which helps you make smart decisions based on data, showing the practical value of data science in finance.

Throughout each project, we'll leverage the strengths of both Copilot and ChatGPT to demonstrate how these AI tools can not only speed up your coding process but also improve the quality of your work.
You will observe how Python may solve a problem quickly, but R struggles, and vice-versa.

This course is perfect for those looking to enhance their data science skills with the power of AI.

About me:

As a consultant who has meticulously analyzed the impact of these tools, I've observed firsthand the tangible benefits they bring to complex projects.

Even in scenarios where tasks seem inherently resistant to optimization, the intelligent assistance provided by Copilot and ChatGPT can lead to substantial time savings.

On average, I save at least one hour per day while tackling complex challenges that would typically demand extensive effort. This efficiency gain is not just about completing tasks faster; it's about achieving a higher standard of work with the insightful, AI-driven suggestions that these tools offer, transforming the way we approach problem-solving in data science.