module #1 Introduction to Data Science Pangkalahatang-ideya ng data science, kahalagahan, at mga aplikasyon
module #2 Data Science Process Pag-unawa sa proseso ng data science:depinisyon ng problema, pangongolekta ng data, paglilinis, pagsusuri, at visualization
module #3 Python for Data Science Introduction to Python programming language at mga library nito para sa data science (NumPy, Pandas, atbp.)
module #4 Data Preprocessing Handling missing values, data normalization, feature scaling, at data transformation
module #5 Data Visualization Introduction to data visualization using Matplotlib and Seaborn
module #6 Descriptive Statistics Measures of central tendency, variability, and data distribution
module #7 Inferential Statistics Hypothesis pagsubok, mga agwat ng kumpiyansa, at p-values
module #8 Pagsusuri ng Pagbabalik Simple at maramihang linear na regression, mga pagpapalagay ng regression, at pagsusuri ng modelo
module #9 Feature Engineering Mga diskarte sa pagpili, pagkuha, at paggawa ng feature
module #10 Supervised Learning Introduction to supervised learning, classification, and regression
module #11 Unsupervised Learning Introduction to unsupervised learning, clustering, and dimensionality reduction
module #12 Model Evaluation Mga Sukatan para sa sinusuri ang performance ng modelo, overfitting, at underfitting
module #13 Decision Trees and Random Forests Introduction to decision trees and random forests, advantages, and limitations
module #14 Support Vector Machines Introduction to support vector machines, kernel trick, at mga uri ng SVM
module #15 Neural Networks Introduction to neural networks, perceptron, and multilayer perceptron
module #16 Deep Learning Introduction to deep learning, convolutional neural networks, at recurrent neural networks
module #17 Natural Language Processing Introduction to natural language processing, text preprocessing, and text representation
module #18 Big Data and NoSQL Databases Introduction to big data, Hadoop ecosystem, at NoSQL databases
module #19 Data Storytelling Epektibong komunikasyon ng mga insight at resulta gamit ang data visualization at storytelling
module #20 Data Science Tools and Technologies Introduction to data science tools and technologies, Jupyter Notebooks, and Git
module #21 Case Study 1:Regression Analysis Paglalapat ng regression analysis sa isang real-world na problema
module #22 Case Study 2:Classification Apping classification techniques to a real-world problem
module #23 Case Study 3:Clustering Paglalapat ng mga diskarte sa clustering sa isang totoong problema sa mundo
module #24 Pagtatapos ng Kurso at Konklusyon Pagpaplano ng mga susunod na hakbang sa karera ng Data Science
Handa nang malaman, ibahagi, at makipagkumpetensya?
