Here has more details: https://docs.google.com/document/d/1cdG9zX5d8laTuqudmuNN9E4c4FX1u_vasseCc2Fbuk4/edit?usp=sharing Lecture : PlaY Data Timeline : [Talk 10 min] Asking Questions & Get the Solutions [Hands-on Orange 40 min] Typical Problem-Solving Skills in MLDM [Break 10 min] [Talk 15 min] A Lighting Talk in Data Sciience [Hands-on Pandas 80 min] Preprocessing before Machine Learning & Data Mining [Break 10 min] [Hands-on Matplotlib 50 min] Visualization Skills [Talk 10 min] A Lighting Talk in Visualization [Break 10 min] [Hands-on sklearn 40 min] PlaY Data with Scikit-Learn [Break 5 min] [Hands-on sklearn&scipy 80 min] PlaY Natural Language Processing (with PTT corpus) Environment Settings: Required Python Packages: PyMongo Orange pandas matplotlib scikit-learn numpy & scipy jieba nltk gensim cv2 (OpenCV) Other Requirements: mongodb OpenCV Required Skills: Linear Algebra Multivariate Calculus Basic Probability Basic Python Manipulation (optional) some basic concept in Convex optimization & Discrete Optimization (optional) some basic concept in Machine Learning or Data Mining (optional) some basic concept in Image Processing & Digital Signal Processing (optional) some basic concept in Natural Language Processing