COURSE CURRICULUM

The program provides a comprehensive exploration of data science, focusing on key areas such as machine learning, data analysis, ethical and legal concerns, and hands-on project work. The Modelling, Regression, and Machine Learning module introduces students to algorithmic foundations for handling large datasets and learning systems. This includes classification algorithms, feature space representation, and managing model fitting using statistical theory. The Visual Data Analysis module teaches students how to design and evaluate interactive visualizations for data analysis, equipping them with the skills to work with data visualization tools and programming libraries.The Applied Data Analytics: Tools, Practical Big Data Handling, Cloud Distribution module deepens students' knowledge of data mining and machine learning algorithms using Python and R. It also introduces cloud computing systems like OpenStack, Hadoop, and Spark, enabling students to manage and analyze big data. The Legal, Ethical, and Security Aspects of Data Management module highlights the importance of privacy, data protection, and security in data science. It covers legal issues such as data ownership, licensing, and information security, preparing students to navigate the ethical and regulatory aspects of data management.Finally, the Individual Data Science Project gives students the opportunity to apply their learned techniques to real-world data science challenges. Students plan and execute research projects, critically analyze results, and present findings in both written and oral formats. These modules collectively prepare students for careers in data science by combining theoretical knowledge, practical skills, and ethical considerations, ensuring they can handle the complexities of big data and contribute meaningfully to the field.