Every course has three parts:Part 1 · LessonsPart 2 · Problems with solutionsPart 3 · Practice
ADV · APDS
Readable Code & Python for Data Science
17 lessons from The Art of Readable Code, OOP and design patterns, LoRA fine-tuning.
EDAExploratory Data Analysis & Unsupervised Learning
Univariate and bivariate analysis, data quality, graph gallery and revision sheet.
NLPNeural Networks, Mathematically
From a single neuron to language models, with PyTorch code and both homeworks.
TSTime Series Analysis & Forecasting
Chapters 1–3 with datasets, TD/TP workbooks, 66 practice questions and flashcards.
WRInformation Web Retrieval & Analytics
Search engines, BoW and n-grams, inverted index, TF-IDF and the vector space model, with labs.
ENGLISHEnglish · Reading & Writing
Unit reading texts and writing homework, with your essays reviewed.