Schedule #

Important
All deadline and due dates in this course will be at AoE time zone. For all dates used in this course, their times are 23:59 Anywhere on Earth (11:59 pm AoE). For example, a due date of “January 8” is the same as “January 8, 23:59pm AoE”. Convert the times to your local times using a Time Zone Converter.

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Week	Dates	Topics	Homework	Quizzes	Readings
1	5/12 - 5/16	Course introduction Text data preprocessing: Normalization, lemmatization, stemming, stop words removal… Text Representations: One hot encoding BoW (frequency counting) TF-IDF	HW1 out 5/16	Quiz 0 \| Knowledge-based \| out 5/12 - due 5/16	Chapter 1 Introduction to Natural Language Processing by Jacob Eisenstein Chapter 2.1 Introduction to Natural Language Processing by Jacob Eisenstein
2	5/19 - 5/23	Classification Introduction Naive Bayes Classification Model Evaluation: accuracy, precision, recall, confusion matrix		Quiz 1 \| week 1\| out 5/16 - due 5/23	Chapter 2.2 Introduction to Natural Language Processing by Jacob Eisenstein
3	5/26 - 5/30	Memorial Day Institute Holiday Logistic Regression SVM Perceptron	HW1 due 5/30 HW2 out 5/30	Quiz 2 \| week 2\| out 5/23 - due 5/30	Chapters 2.3, 2.4, 2.5 Introduction to Natural Language Processing by Jacob Eisenstein.
4	6/02 - 6/06	SVD (Dimensionality Reduction) + Co-occurrence embeddings Glove		Quiz 3 \| week 3\| out 5/30 - due 6/06	GloVe: Global Vectors for Word Representation
5	6/09 - 6/13	Neural Network (fully connected) Word2vec: CBoW, Skip-Gram Toolbox on Classification Algorithms Toolbox on Word2Vec	HW2 due 6/13 HW3 out 6/13	Quiz 4 \| week 4\| out 6/06 - due 6/13	NN Playground Interactive NN initialization; The role of a hidden layer; Back propagation numerical example; More detailed introduction; Efficient Estimation of Word Representations in Vector Space
6	6/16 - 6/20	Juneteenth Institute Holiday CNN RNN Toolbox on CNN For Text Classification		Quiz 5 \| week 5\| out 6/13 - due 6/20	CNN Live Demo; A guide to an efficient way to build CNN and optimize its hyper-parameters; Back Propagation in CNN; Transfer learning in CNN;
7	6/23 - 6/27	LSTM and GRU LSTM + Attention (Focus on Attention mechanism)		Quiz 6 \| week 6\| out 6/23 - due 6/27
8	6/30 - 7/04	Transformer models Examples: BERT(Bidirectional Encoder Representations from Transformers) and GPT (Generative Pre-trained Transformer) Independe Day Institute Holiday	HW3 due 7/04 Note: You may submit HW3 without penalty until 7/07 H4 out 7/04	Quiz 7 \| week 7\| out 6/27 - due 7/04 ( Note: You may submit Quiz 7 without penalty until 7/07 )	Attention Is All You Need; BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding;
9	7/07 - 7/11	Sequence Labelling: POS Tagging Sequen1e Labelling: NER		Quiz 8 \| week 8\| out 7/04 - due 7/11
10	7/14 - 7/18	Unsupervised Models Topic Modeling (Latent Semantic Indexing, LDA (Latent Dirichlet Allocation) Toolbox on Exploring LLMs		Quiz 9 \| week 9\| out 7/11 - due 7/18
11	7/21 - 7/22	Introduction to Generative AI Prompt Engineering Techniques Retrieval Augmented Generation (RAG)	HW4 due 7/25	Quiz 10 and Quiz 11 \| week 10 & 11 \| out 7/18 - due 7/25