Review the main explanations offered by strategic management research, economics and business related fields with regard to differences in firm behavior and performance. To do so, we will examine a list of articles that refer to the related key topics in strategy research. Critically analyze and comment theoretical and empirical issues in strategy from an interdisciplinary perspective. - Integrate existing knowledge to develop an original research proposal with an interesting research question and testable propositions. - Develop skills to present and defend your research proposal, and ideas more generally. Learn how to review a research paper.

Course Description: This comprehensive data science course is designed to take students from beginner to advanced levels, equipping them with the necessary skills to excel in data-driven industries. Through hands-on projects, students will learn to manipulate data, build machine learning models, and effectively communicate insights. Whether you're looking to break into the tech industry or upskill in your current role, this course will provide you with the practical experience and theoretical knowledge needed to succeed. Course Objectives: Understand core data science concepts and their applications. Learn to collect, clean, and preprocess data. Develop strong programming skills in Python and R. Build and evaluate machine learning models. Gain proficiency in data visualization and storytelling. Apply statistical and predictive modeling techniques. Work on real-world projects to build a strong portfolio. Target Audience: Aspiring data scientists and analysts. Professionals looking to transition into data science. University students in STEM fields. Entrepreneurs interested in leveraging data for business growth. Prerequisites: Basic knowledge of programming (Python or R preferred). Understanding of basic mathematics and statistics. A laptop capable of running data science tools.

Course Description: This specialized course focuses on the emerging field of prompt engineering, a critical skill for maximizing the efficiency and accuracy of AI language models. Students will learn techniques to craft effective prompts for AI tools like GPT, Claude, and Bard to achieve desired results across various applications, from content creation to data analysis. By the end of the course, participants will be able to design optimized prompts to enhance AI-driven projects and workflows. Course Objectives: Understand the fundamentals of AI language models and their applications. Develop the skills to write precise and effective prompts. Learn to troubleshoot and refine AI interactions. Explore use cases in industries like marketing, data science, and creative writing. Gain hands-on experience with leading AI platforms. Target Audience: Developers and AI enthusiasts. Content creators and marketers. Data analysts and business professionals. Anyone interested in leveraging AI tools effectively. Prerequisites: Basic understanding of AI concepts (recommended but not required). Interest in AI-driven applications and tools.