Skills

Skills and expertise developed through coursework at AIMS Senegal and practical experience.

Data modelling, EDA, tabular data manipulation, time series feature extraction, and text preprocessing pipelines.

Web scraping with BeautifulSoup, Selenium, and WebScraper; KoboToolbox survey forms; and Pandas-based data cleaning.

Supervised and unsupervised learning, regularisation, ensemble methods, SVMs, and model evaluation techniques.

Neural network architectures, CNNs, RNNs, LSTMs, GRUs, gradient descent, regularisation, and real-world DL applications.

Advanced multidimensional methods including SOMs, association rules, correspondence analysis, and component-based regression.

Linear and nonparametric regression, Principal Component Analysis, and Singular Value Decomposition for high-dimensional data.

CNNs, image pipelines, anomaly detection, transfer learning, object detection, segmentation, and vision transformers.

Classic NLP, word embeddings, RNNs, transformer architecture, LLMs, and applications including summarisation and chatbots.

ER modelling, relational design, normalisation, SQL for data science, NoSQL with MongoDB, and Big Data distributed systems.

NetCDF data, CDO, Bash scripting, Python climatology, PCA, Self-Organising Maps, and wavelet-based time series analysis.

Web architecture, REST & SOAP services, XML/JSON, Android concepts with Flutter basics, and SQL/PostgreSQL databases.