There has been an explosion of information about AI recently. News feeds are filled with articles, videos, and discussions about artificial intelligence. But is AI truly as popular as it appears, or does it only feel that way because those who are interested naturally notice it more?
At the same time, YouTube has emerged as one of the most effective platforms for promoting IT products. Video content allows creators to share visual demonstrations, step-by-step tutorials, and in-depth reviews that help build trust and understanding. For companies developing AI, machine learning, or technology solutions, finding the right channels to showcase their work is critical.
In this context, I launched this project to analyze current trends in AI-related content on YouTube, identify promising channels in the field, and provide data-driven recommendations to help small businesses and marketers choose the most suitable partners for advertising and collaboration.
This stage clarify the problem, determine target viewer and create some question we may need to answer to solve the problem
detail the origin and nature of the data to be used, ensuring it aligns with the problem definition and allowing for effective analysis of AI content trends on YouTube.
Outline the methodological approach and architecture for the data analysis, including the tools, techniques, and models planned to extract insights and generate recommendations.
This page would describe the practical execution of the designed solution, detailing the steps taken to collect, process, analyze the YouTube data, and generate the initial findings..
Summarize the key insights derived from the analysis, present the data-driven recommendations for YouTube channels, and discuss the implications for businesses and marketers.