AI Fundamentals for Researchers is designed to equip participants with foundational knowledge in artificial intelligence, tailored specifically for those engaged in research-related fields. This course emphasizes practical applications and hands-on projects, ensuring that learners can translate theoretical concepts into real-world solutions. Participants will engage in interactive learning experiences that foster collaboration and innovation, culminating in the opportunity to publish their findings in Cademix Magazine, thereby enhancing their professional visibility.
The curriculum is structured to cover a wide array of essential topics that are critical for understanding AI’s role in research. By the end of the course, participants will have developed a comprehensive skill set that includes not only theoretical knowledge but also practical experience through project work. This blend of learning will empower graduates to leverage AI technologies effectively in their respective domains, enhancing their research capabilities and career prospects.
Introduction to Artificial Intelligence: Definitions and Key Concepts
Overview of Machine Learning and its Applications
Understanding Neural Networks and Deep Learning
Data Preparation and Feature Engineering Techniques
Introduction to Natural Language Processing (NLP)
Basics of Computer Vision and Image Processing
AI Tools and Frameworks: A Practical Guide
Designing and Implementing AI Models
Evaluating AI Model Performance and Metrics
Final Project: Developing an AI Solution for a Research Problem