AI and Machine Learning
This course is a technical approach to cutting-edge AI methods. Students will productionize machine learning models to solve business problems, evaluate modern AI use cases (such as computer vision) and adapt Large Language Models (LLMs) for specific applications.
Course Topics
Textual Insights – NLP and Sentiment Analysis
Dive into the world of Natural Language Processing, understanding its foundational concepts, and exploring techniques to conduct sentiment analysis, turning text into actionable insights.
The Visual Side of AI – Introduction to Computer Vision
Introduce students to computer vision principles, showcasing how machines interpret and analyze images and videos, laying a foundation for more advanced visual AI studies.
Revolutionizing NLP – Transformers and Large Language Models
Explore the mechanics and advantages of transformers, understanding their architecture, and the power of modern large language models, such as ChatGPT, which have revolutionized tasks across the AI spectrum.
Crafting Dynamic System – Building Responsive AI Solutions
Emphasize the importance of creating AI systems that are not just smart, but also responsive and adaptable to real-world scenarios, ensuring user satisfaction and system efficiency.
Navigating the AI Minefield – Assessing AI Risks
Equip students with the tools and knowledge to assess the risks associated with deploying AI solutions, from bias in training data to unforseen behavior in deployed models.
Staying Ahead – Adapting to New AI Trends
Encourage a mindset of continuous learning and adaptation, introducing students to current AI trends and emphasizing the importance of styaing updated in this rapidly evolving field.
400
Disclosure
This course is delivered online through an institution of the Lower Cost Models Consortium (LCMC) that is different than your degree-granting institution that awards the academic credit for the course.
