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Data Science Methods and Techniques [2024] - Printable Version

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Data Science Methods and Techniques [2024] - AD-TEAM - 04-22-2025

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Data Science Methods and Techniques [2024]
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 17h 2m | 7.05 GB
Instructor: Henrik Johansson

Learn Data Science Methods and Techniques for Data Analysis and Machine Learning [2024]

Description

Welcome to the course Data Science Methods and Techniques for Data Analysis and Machine Learning!

Data Science is expanding and developing on a massive and global scale. Everywhere in society, there is a movement to implement and use Data Science Methods and Techniques to develop and optimize all aspects of our lives, businesses, societies, governments, and states.

This course will teach you a large selection of Data Science methods and techniques, which will give you an excellent foundation for Data Science jobs and studies. This course has exclusive content that will teach you many new things regardless of if you are a beginner or an experienced Data Scientist, Data Analyst, or Machine Learning Engineer.

This is a three-in-one master class video course which will teach you to master Regression, Prediction, Classification, Supervised Learning, Cluster analysis, and Unsupervised Learning.

You will learn to master Regression, Prediction and supervised learning. This course has the most complete and fundamental master-level regression content packages on Udemy, with hands-on, useful practical theory, and also 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.

You will learn to master Classification and 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.

You will learn to master Cluster Analysis and unsupervised learning. This part of the course is about unsupervised learning, cluster theory, artificial intelligence, explorative data analysis, and some useful Machine Learning clustering algorithms ranging from hierarchical cluster models to density-based cluster models.

You will learn
  • Knowledge about Data Science methods, techniques, theory, best practices, and tasks
  • Deep hands-on knowledge of Data Science and know how to handle common Data Science tasks with confidence
  • Detailed and deep Master knowledge of Regression, Prediction, Classification, Supervised Learning, Cluster Analysis, and Unsupervised Learning
  • Hands-on knowledge of Scikit-learn, Statsmodels, Matplotlib, Seaborn, and some other Python libraries
  • Advanced knowledge of A.I. prediction models and automatic model creation
  • Cloud computing: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resources
  • Option: To use the Anaconda Distribution (for Windows, Mac, Linux)
  • Option: Use Python environment fundamentals with the Conda package management system and command line installing/updating of libraries and packages - golden nuggets to improve your quality of work life
  • And much more.

This course includes
  • an easy-to-follow guide for using the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). You may learn to use Cloud Computing resources in this course
  • an easy-to-follow optional guide for downloading, installing, and setting up the Anaconda Distribution, which makes anyone able to install a Python Data Science environment useful for this course or for any Data Science or coding task
  • content that will teach you many new things, regardless of if you are a beginner or an experienced Data Scientist, Data Analyst, or Machine Learning Engineer
  • a large collection of unique content, and this course 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

This course is an excellent way to learn to master Regression, Prediction, Classification, and Cluster analysis!

These are the most important and useful tools for modeling, AI, and forecasting.

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 a Ph.D. or no education or experience at all

This course is the course we ourselves would want to be able to enroll in if we could time-travel and become new students. In our opinion, this course is the best course to learn to Master Regression, Prediction, Classification, Supervised Learning, Cluster analysis, and unsupervised learning.

Course requirements
  • Basic knowledge of the Python programming language and preferably the Pandas library
  • The four ways of counting (+-*/)
  • Everyday experience using a computer with either Windows, MacOS, iOS, Android, ChromeOS, or Linux is recommended
  • Access to a computer with an internet connection
  • The course only uses costless software
  • Walk-you-through installation and setup videos for Cloud computing and Windows 10/11 is included

More Info

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