American University of Beirut

​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​Artificial Intelligence (AI) is revolutionizing the field of medicine, and many medical institutions are incorporating AI into their daily operations. AI has been found to improve diagnostic accuracy, treatment planning, and patient outcomes, and reduce healthcare costs. With the increasing adoption of AI in healthcare, it is becoming increasingly essential for medical providers and researchers to learn AI and related technologies.

Programming is an important skill a medical student can acquire proficiency in. Python is a powerful, high-level, and easy-to-learn programming language that is widely used in the field of data science and machine learning. Learning Python provides a solid foundation for researchers to progress to data science and machine learning.

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Data science is an interdisciplinary field that involves the use of statistical methods, computer science, and domain expertise to extract insights and knowledge from data. Researchers who are proficient in data science can analyze large datasets, find patterns, and make predictions based on data. They can also develop predictive models for disease diagnosis and treatment planning.

Machine learning is a subfield of AI that involves training machines to learn from data and make predictions or decisions without explicit instructions. A medical researcher who is proficient in machine learning can develop algorithms that can analyze and interpret medical data, identify patterns and anomalies, and make predictions based on patient data.

Deep learning is a subfield of machine learning that involves training artificial neural networks to learn from data and make decisions based on that data. Deep learning is particularly well-suited to the analysis of medical images, such as X-rays and MRI scans. A medical researcher who is proficient in deep learning can develop algorithms that can accurately detect and diagnose diseases from medical images.​

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Interested researchers should learn Python, data science, machine learning, and deep learning in that order, as these skills are becoming increasingly important in the field of medicine.

There are plenty of free resources online to learn data science, machine learning, and deep learning. Here is a compilation of playlists that any beginner can follow in the order outlined above to become proficient in data science and AI. Credits to CodeBasics and Patrick Loeber.​

1. Python Tutorial Playlist
   
2. Data Analysis Playlist (Pandas Tutorial)
   
3. Machine Learning Playlist
   
4. Deep Learning Playlist
   
5. Advanced Deep Learning using PyTorch​
   

To be part of the AIM programming team, one must prove basic literacy in data analysis, machine learning, and deep learning.

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