Hi,

This week you'll learn about Computer Vision and Deep Learning for Education.

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In our previous posts, we learned about the benefits, applications, and challenges of computer vision and deep learning for big industries and businesses. Today's tutorial discusses the necessities, benefits, applications, and challenges of using deep learning and computer vision in education.

The big picture: Globally, it is estimated that around 750 million adults are still functionally illiterate, making it a tremendous challenge to adequately prepare the workforce for rapid technological change requiring continual reskilling. Artificial intelligence (AI) has great potential to enable them to keep up with changing technologies and remain valuable to the country. 

Furthermore, in emerging markets, AI has the potential to provide affordable post-secondary education, make learning exciting and fun, and make the content personalized to individual students' needs. 

How it works:  Intelligent tutoring systems can teach learners by giving them immediate and personalized feedback and providing insights into their progression. They can tailor and individualize the learning pathway such that it is specifically designed to accommodate their strengths, weaknesses, talents, and challenges. AI can ingest data from sources like performance reports, attendance, and reports from teachers and counselors and create alerts that can help the institution support students in need of assistance, in danger of dropping out, or undergoing mental health, academic, or personal life crisis. AI can also help enforce parent engagement by allowing them to become participants rather than just reviewers in their child's educational journey. 

Our thoughts: AI can help teachers and research experts create innovative and personalized content for their students. It can easily handle repetitive, manual tasks (e.g., checking homework, grading tests, organizing research papers, maintaining reports, and making presentations or notes). AI- and ML-powered software can also deliver widely available and affordable opportunities for students to upskill.

Yes, but: AI in the education sector comes with its challenges. In addition, the lack of technical expertise required to integrate AI solutions that involve complex algorithms has also hampered the growth of the AI market. AI in education will raise concerns regarding student data privacy, protection, and ethical use. Furthermore, not having decent smartphones and internet access can disadvantage students in this digital age. With no smartphones, access to the information required to train unbiased machine learning (ML) models will be limited.

Stay smart: It is essential to understand the risks and challenges associated with AI and their enormous potential when using AI algorithms in this sector.

Click here to read the full tutorial

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