This chapter aims to explore the use of English as a Medium of Instruction (EMI) in Algerian universities, focusing on students’ sentiments towards its implementation. As the Algerian Ministry of Higher Education increasingly prioritizes English, understanding student opinions becomes crucial for effective policy-making. Three research questions guided this study: (1) What is the polarity of the students’ sentiments towards EMI implementation? (2) Are their sentiments subjective or objective? (3) What key themes emerge from their responses and how do they relate to their sentiments? Thirty-four participants, from the University Centre of Mila, were asked to contribute their opinion thereof. Employing Natural Language Processing (NLP) and Sentiment Analysis techniques in Python, the study run NLP computational tasks to determine students’ sentiments, ending up with a thematic analysis. Visualizations were plotted to represent text data visually. The findings, while predominantly positive, revealed a mix of sentiments: while students generally support EMI, they have concerns about its implementation, especially regarding language preparedness and support programs. The analysis also identified key themes, including the benefits of EMI for global competitiveness and the challenges of transitioning to English. These results offer practical insights for policymakers and educators, highlighting the need for targeted training and phased implementation. They also provide a deeper understanding of the dynamics of EMI in the Algerian context through the lens of state-of-the-art unsupervised machine learning methods. Given the small sample size, this study serves as a pilot, laying the groundwork for larger-scale research to refine these findings and address broader contexts.