This project is a data analysis of the "Krish Naik" YouTube channel, with a focus on identifying key metrics and learning at viewvers behaviour.

• Overview
• Data Sources
• Data Analysis
• Findings and Conclusion

The "Krish Naik" YouTube channel is a educational channel with around 2000 videos, dedicated to sharing data science(AI, ML, DL), statistics and programming content. The goal of this project is to analyze the response on the channel and identify users interest.

The data for this analysis was collected using the YouTube API V3, which provides access to a wide range of data on YouTube channels and videos. The data includes information on video views, watch time, subscribers.

The data was analyzed using Python, with the Pandas, Matplotlib and Seaborn libraries used for data manipulation and visualization. The analysis included the following steps:

Data cleaning and preparation: The data was cleaned and prepared for analysis, including removing duplicates, handling missing values, and converting data types as needed.

Exploratory data analysis: The data was visualized using various charts and graphs to identify trends and patterns in the data.

Key metrics analysis: Key metrics such as views, watch time,subscribers were analyzed to identify the most popular videos.

Based on the analysis, the following findings and recommendations were made:

• The most popular videos on the channel are those with basic introductions to any topic such as difference between AI vs ML vs DL. The channel should consider creating more content in this niche.

• This project provides valuable insights into the performance of the YouTube channel, with recommendations for improving content. The use of data analytics tools and techniques can help channel owners and content creators make data-driven decisions and improve the performance of their channels.