This course is designed to give you a deep understanding of Data Mining and Big
Data. It focuses on both the theory and practical applications of data analysis,
helping you become proficient in using these technologies to tackle real-world
challenges in Kenya and beyond. This course will provide you with the skills to
apply data mining and big data techniques in key sectors like agriculture,
healthcare, finance, and governance. The course also explores the ethical
considerations of working with large datasets, emphasizing responsible data
handling in the context of the global and local Kenyan economy.

CLO 1: Describe the various techniques of data mining and big data analytics.

CLO 2: Use tools and techniques of big data analytics in preparation, analysis and interpretation of real-world data.

CLO 3: Choose appropriate techniques to analyze and interpret big data.

CLO 4: Assess legal and ethical considerations surrounding malware analysis.

Overview of Data Mining and Big Data: Algorithmic aspect of data mining; high-dimensional database indexing; OLAP; data reduction; machine learning in data mining; Data mining tools; data analytics tools; Data mining techniques: Association rules mining; classifier induction; cluster analysis; outliers/deviants detection; Text mining; sentiment analysis; Image and video mining; Web mining and social network analysis; Big Data Technologies: Distributed computing principles; Hadoop HDFS and MapReduce; NoSQL; Apache Spark; Data warehousing and data lakes; Theory and methods for big data analytics: machine learning and data mining methods for big data; dimensionality reduction; locality sensitive hashing; statistical analysis techniques; data-streaming processing; Big data analytics applications: social network analysis; Recommendation systems; spam analysis; fraud analytics, customer segmentation; Data Ethics and Privacy: Ethical considerations in data mining; Data protection regulations; Privacy-preserving data mining techniques;