Machine Learning and AI: Large language models, natural language processing (BERT, NLTK), computer vision, neural networks (CNNs and RNNs), XGBoost, random forests, clustering, support vector machines, Naive Bayes, and Skip-gram. Data Engineering and Cloud: Databricks, Apache Spark (PySpark), Hadoop, MapReduce, ETL, AWS EC2, Google Cloud Platform, Docker, PostgreSQL, MySQL, NoSQL databases, and object-relational mapping.