Data Science and Machine Learning Fundamentals | Udemy

This course is an exciting hands-on view of the fundamentals of Data Science and Machine Learning

Data 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 Udemy courses in terms of education and value.

You will learn about

• Regression and Prediction with Machine Learning models using supervised learning. This course has the most complete and fundamental master-level regression content packages on Udemy, 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 Classifiers 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 and Pandas for data handling.

This course includes

• a 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.
• an easy-to-follow guide for downloading, installing, and setting up the Anaconda Distribution, which makes anyone able to install the Python Data Science and Machine Learning environment for this course.
• 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 Udemy.
• 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 requirements

• The four ways of counting (+-*/)
• Basic everyday experience with either Windows, Linux, Mac OS, or similar operating systems

After completing this course, you will have

• Knowledge 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.
• Master Python and 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.