Data scientist / machine learning engineer / data engineer

Assistant student in the Linguistic Services department of the University of
Barcelona.

Topics covered:
Natural Language Processing: sentiment analysis, document classification
NER, word2vec, LSTMs (Python, Pandas, Numpy, Pandas, PyTorch, NLTK,
CoreNLP).

Machine Learning: linear and logistic regression, SVM, k-NN, K-means,
decision trees (Python, Numpy, Pandas, SciKit-Learn).

Deep Learning: CNNs, RNNs, Variational Auto-Encoders, GANs,
Reinforcement Learning (Python, Numpy, Pandas, PyTorch).

Data Science: data analysis and manipulation, SQL, algorithmic complexity,
graphs/networks (Python, Seaborn, Pandas, MySQL, Apache Hadoop).

Algebra, Calculus, and Probability: optimization techniques, information
theory, probability, hypothesis testing (Python, SciPy, Matlab).

AI techniques: uninformed, informed, and adversarial search, semantic
networks, ontologies, fuzzy systems, Bayesian networks (Python).

Topics covered:
Computational Linguistics: N-gram models, PoS Tagging (Python, NLTK).

Statistical Methods and Techniques: Experimental design, linear regression,
hypothesis testing, ANOVA (SPSS).

Cognitive Neuroscience

Language Evolution and Neurolinguistics

Theoretical and Empirical Linguistics

Logics (classic and non-classic)

Philosophy of Maths

Philosophy of Mind and Language

Moral Philosophy

Political Philosophy