Last updated 5/2025 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 55h 41m | Size: 22.7 GB
Learn to master Data Science and Machine Learning Fundamentals with Python and Pandas
What you'll learn
Knowledge about Data Science and Machine Learning theory, algorithms, methods, best practices, and tasks
Deep hands-on knowledge about Data Science and Machine Learning, and know how to do common Data Science and Machine Learning tasks
The ability to handle common Data Science and Machine Learning tasks with confidence
Master Python for Data Handling
Master Pandas for Data Handling
Knowledge and practical hands-on knowledge of Scikit-learn, Statsmodels, Matplotlib, Seaborn, and many other Python libraries
Detailed and deep, Master knowledge of Regression, Regression Analysis, Prediction, Classification, and Cluster analysis
Advanced knowledge of A.I. prediction models and automatic model creation
Advanced Knowledge of Text Mining, Text Mining Tasks, and Emotion Mining
Cloud computing: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resources
Requirements
The four ways of counting (+-/)
Everyday experience with Windows, Linux, or MacOS
Description
This course is an exciting hands-on view of the fundamentals of Data Science and Machine LearningData Science and Machine Learning are developing on a massive scale. Everywhere you look in society, the world wide web, or in technology, you will find Data Science and Machine Learning algorithms working behind the scenes to analyze and optimize all aspects of our lives, businesses, and our society. Data Science and Machine Learning with Artificial Intelligence are some of the hottest and fastest-developing areas right now. This course will teach you the fundamentals of Data Science and Machine Learning. This course has exclusive content that will teach you many new things regardless of if you are a beginner or an experienced Data Scientist, and aspires to be one of the best courses in terms of education and value. You will learn aboutRegression and Prediction with Machine Learning models using supervised learning. This course has the most complete and fundamental master-level regression analysis content packages on , with hands-on, useful practical theory, and automatic Machine Learning algorithms for model building, feature selection, and artificial intelligence. You will learn about models ranging from linear regression models to advanced multivariate polynomial regression models.Classification with Machine Learning models using supervised learning. You will learn about the classification process, classification theory, and visualizations as well as some useful classifier models, including the very powerful Random Forest Classifier Ensembles and Voting Classifier Ensembles.Cluster Analysis with Machine Learning models using unsupervised learning. In this part of the course, you will learn about unsupervised learning, cluster theory, artificial intelligence, explorative data analysis, and seven useful Machine Learning clustering algorithms ranging from hierarchical cluster models to density-based cluster models.The fundamentals of Data Science and Machine Learning. This course gives a very solid foundation and knowledge base for Data Science and Machine Learning jobs or studies.Advanced A.I. prediction models and automatic model creation. This video course includes videos where the use of very powerful algorithms for automatic model creation is taught.Advanced Text Mining and Automation. You will learn to mine text data and the fundamentals of Text and Emotion Mining such as Tokenization, text data preparation, spell checking, lemmatization, stemming, and classification of text data. Mastering Python for data handling.Mastering Pandas for data handling.This course includesa comprehensive and easy-to-follow teaching package for Mastering Python and Pandas for data handling, which makes anyone able to learn the course contents regardless of beforehand knowledge of programming, tabulation software, Python, Pandas, Data Science, or Machine Learning.Learn to use Cloud computing: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resourcesan optional easy-to-follow guide for downloading, installing, and setting up the Anaconda Distribution, which makes anyone able create a local installation of a Python Data Science and Machine Learning environment.content that will teach you many new things, regardless of if you are a beginner or an experienced Data Scientist.a large collection of unique content, and will teach you many new things that only can be learned from this course on .A complete masterclass package for Data Science and Machine Learning.A course structure built on a proven and professional framework for learning.A compact course structure and no killing time.Is this course for you?This course is for you, regardless if you are a beginner or an experienced Data Scientist. This course is for you, regardless if you have no education or are experienced with a Ph.D.Course requirementsThe four ways of counting (+-/)Basic everyday experience with either Windows, Linux, Mac OS, or similar operating systemsAfter completing this course, you will haveKnowledge about Data Science and Machine Learning theory, algorithms, methods, best practices, and tasks.Deep hands-on knowledge of Data Science and Machine Learning, and know how to do common Data Science and Machine Learning tasks.The ability to handle common Data Science and Machine Learning tasks with confidence.Knowledge to Master Python for Data Handling.Knowledge to Master Pandas for Data Handling.Knowledge and practical hands-on knowledge of Scikit-learn, Stats models, Matplotlib, Seaborn, and many other Python libraries.Detailed and deep Master knowledge of Regression Prediction, Classification, and Cluster Analysis.Advanced knowledge of A.I. prediction models and automatic model creation.Advanced Knowledge of Text Mining, Text Mining Tasks, and Emotion Mining.
Who this course is for
This course is for you, regardless if you are a beginner or experienced Data Scientist, regardless if you have a Ph.D., or no education or experience at all.
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