Artificial Intelligence & Machine Learning

This course explores the ethical challenges and societal impacts posed by the development and deployment of Artificial Intelligence (AI). Students will examine key issues such as bias and fairness, privacy and surveillance, accountability, job displacement, and the ethical dilemmas surrounding autonomous systems. Through case studies, discussions, and critical analysis, the course emphasizes the importance of responsible AI design and use, equipping students with the tools to evaluate and address the ethical considerations that arise in diverse AI applications across industries. Students will also explore frameworks and regulations designed to guide ethical AI practices globally.

This course strengthens intermediate Python skills for AI workflows, data analysis, and industry-ready automation. Students practice data wrangling with pandas; exploratory data analysis and visualization with matplotlib and seaborn; feature engineering and model preparation; working with APIs and basic automation; building and interpreting baseline ML models using scikit-learn and xgboost; and operating in cloud-based Jupyter environments. The course culminates in a portfolio-ready applied project aligned to local industry use cases.

This course introduces core concepts and applications of artificial intelligence and machine learning. Students explore key workloads, including anomaly detection, computer vision, natural language processing, and knowledge mining, while learning to prepare data, train models, and evaluate results. Hands-on activities include applying AI tools for image recognition, text analysis, and speech processing, as well as experimenting with generative AI and large language models. The course also addresses ethical and responsible AI principles, including privacy, safety, transparency, and accountability in AI solutions.
 

This course examines how artificial intelligence and automation technologies can be leveraged to develop intelligent, data-driven solutions. Students will use AI-powered tools to prepare, analyze, and visualize data, build custom applications, design interactive web solutions, and automate business workflows. The course also introduces generative AI development, intelligent assistant design, and AI-assisted software engineering for data analysis, customer support, and security enhancement. By the end, learners will be able to create secure, efficient, and adaptable systems that transform data into actionable insights, thereby improving organizational productivity.