This is the course for you if you want to develop strong foundations and learn advanced Data Mining approaches utilizing industry-standard Machine Learning models and algorithms. It covers all you need to know about Data Mining and its methods, as well as Machine Learning Models and how to use them in practice.

The term "data mining" refers to the process of extracting information from a set of data It is defined as extracting patterns from data and uncovering hidden insights (knowledge) from the database. Data mining is an automated technique that involves looking for patterns in vast datasets that humans might miss.

This course will provide you with advanced data mining knowledge. This course begins by giving you a thorough understanding of the fundamentals of data mining.This course is a one-stop shop for anyone interested in pursuing a career in data mining.

Requirements:

• Basic knowledge required in Statistics.
• Basic knowledge required for Python.
• Passion for Data mining & Machine Learning
• Determination and Desire to Learn new things

Who this course is for:

• People who are quite beginners.
  
• Anyone who is curious to learn Data Mining.
  
• Anyone who is interested in learning Data Mining algorithms.
  
• Data Scientists.
  
• Machine learning experts.
  
• Anyone who wants to explore data science.
  
• Take this course if you want a competitive edge with your tech skills.
  
• Job-seekers
  
• Students and professionals who want to improve the training capabilities

Subtitles: English
Udemy Rating: 4.7/5.0
Enroll here: https://www.udemy.com/course/data-mining-in-data-science-machine-learning/

Standing at the first place among the Best Online Data Mining Courses, Data Mining Specialization offered by University of Illinois at Urbana-Champaign offers data mining techniques for both structured and unstructured data, including both structured and unstructured data in the form of natural language text. Pattern discovery, clustering, text retrieval, text mining and analytics, and data visualization are just a few of the subjects covered in this course. Using a Yelp restaurant review data collection, the Capstone project task is to solve real-world data mining difficulties.

The lecture component of the online Master of Computer Science Degree in Data Science is comprised of courses 2 through 5. Before or after starting the Specialization, you can apply to the degree program.

This course offers:

• Flexible Schedule: Set and maintain flexible deadlines.
  
• Certificate : Earn a Certificate upon completion
  
• 100% online
  
• Intermediate Level
  
• Approx. 8 months to complete: Suggested pace of 4 hours/week
  
• Subtitles: English, Arabic, French, Portuguese (European), Chinese (Simplified), Italian, Vietnamese, Korean, German, Russian, Spanish

Coursera Rating: 4.5/5
Enroll here: https://www.coursera.org/specializations/data-mining

Coming at the second place on the list of the Best Online Data Mining Courses is Pattern Discovery in Data Mining offered by University of Illinois at Urbana-Champaign. You can learn about the fundamentals of data mining, including approaches and applications. Then delve into one of data mining's subfields: pattern discovery. Pattern discovery in data mining is covered in detail, including concepts, methods, and applications.

Learners also go over data-driven phrase mining approaches and some fascinating pattern discovery applications. This course will teach you how to practice and engage in scalable pattern discovery methods on huge transactional data, discuss pattern assessment measures, and investigate methods for mining a variety of patterns, sequential patterns, and sub-graph patterns, among other things.

This course offers:

• Flexible Schedule: Set and maintain flexible deadlines.
  
• Certificate : Earn a Certificate upon completion
  
• 100% online
• Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, Korean, German, Russian, English, Spanish
• Course 4 of 6 in the Data Mining Specialization

Coursera Rating: 4.3/5
Enroll here: https://www.coursera.org//learn/data-patterns

Predictive Analytics and Data Mining offered by University of Illinois at Urbana-Champaign is woth mentioning as it seizes the third position in the list of the Best Online Data Mining Courses. This course introduces students to the science of business analytics while also emphasizing the creative use of numbers in the digital world.

The purpose is to give organizations and managers the foundation they need to use data analytics to solve real-world problems they face on a daily basis. Students will learn how to select the best analytic tool for their purposes, as well as how to collect, analyze, and visualize data in accurate and reliable ways, and how to use data in decision-making for their agencies, companies, or clients.

This course offers:

• Flexible deadlines: Reset deadlines in accordance to your schedule.
  
• Certificate : Earn a Certificate upon completion
  
• 100% online
  
• Intermediate Level
  
• Approx. 24 hours to complete
• Subtitles: French, Portuguese (European), Russian, English, Spanish

Coursera Rating: 4.4/5
Enroll here: https://www.coursera.org/learn/predictive-analytics-data-mining

The University of Illinois at Urbana-Champaign is a global leader in research, teaching, and public engagement, with a diverse range of programs, a strong academic reputation, and internationally renowned faculty and alumni. Illinois contributes to the world by advancing knowledge, preparing students for meaningful lives, and addressing crucial societal issues.

Once you enroll in this course, you are able to learn the fundamentals of cluster analysis before diving into a variety of clustering approaches, algorithms, and applications. This includes partitioning algorithms like k-means, hierarchical algorithms like BIRCH, and density-based algorithms like DBSCAN/OPTICS. Learn methods for clustering validation and clustering quality evaluation as well. Finally, look at several applications that use cluster analysis.

This course offers:

• Flexible deadlines: Reset deadlines in accordance to your schedule.
  
• Certificate : Earn a Certificate upon completion
  
• 100% online
  
• Beginner Level
  
• Approx. 17 hours to complete
  
• Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, Korean, German, Russian, English, Spanish
• Course 5 of 6 in the Data Mining Specialization

Coursera Rating: 4.5/5
Enroll here: https://www.coursera.org/learn/cluster-analysis

Note: You should complete all the other courses in this Specialization before beginning this course.

This six-week Data Mining Specialization Project course will allow you to apply data mining algorithms and techniques learned in previous Specialization courses, such as Pattern Discovery, Clustering, Text Retrieval, Text Mining, and Visualization, to solve interesting real-world data mining challenges. You'll work on a Yelp restaurant review data set, applying all of the knowledge and skills you've gained in past courses to mine this data set for interesting and relevant information. The Project's architecture emphasizes:

• mimicking a data miner's workflow in a real-world scenario;
• integrating diverse mining techniques covered in many individual courses; and
• experimenting with different ways to solve a problem to deepen your understanding of techniques
• allowing you to propose and explore your own creative ideas.

The project's purpose is to evaluate and mine a big amount of Yelp review data in order to uncover helpful information that will assist customers in making dining decisions. A cuisine map can assist people comprehend what cuisines are available and grasp the big picture of all types of cuisines and their relationships. Once they've decided on a cuisine to explore, they'll want to know what the most popular dishes are so they can choose what to eat. Finally, they must select a dining establishment. As a result, recommending eateries based on a specific meal would be beneficial. Furthermore, forecasting the state of a restaurant's hygiene might be beneficial.

This course offers:

• Flexible deadlines: Set and maintain flexible deadlines.
  
• Certificate : Earn a Certificate upon completion
  
• 100% online
  
• Beginner Level
  
• Approx. 11 hours to complete
  
• Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, Korean, German, Russian, English, Spanish
• Course 6 of 6 in the Data Mining Specialization

Coursera Rating: 4.6/5
Enroll here: https://www.coursera.org/learn/data-mining-project

This data mining and machine learning course will equip you with the information you need to understand how firms like Google, Amazon, Youtube, and even Udemy extract meaning and insights from large data sets. In this comprehensive masterclass, you'll discover everything you've always wanted to know about machine learning but were too frightened to ask. There is no need to know how to code.

The "Professional Certificate in Data Mining & Machine Learning" course is proudly presented by the Academy of Computing & Artificial Intelligence. It all began when the expert team of The Academy of Computing and Artificial Intelligence [ACAI] (PhD, PhD Candidates, Senior Lecturers, Consultants, Researchers) and industry experts (PhD, PhD Candidates, Senior Lecturers, Consultants, Researchers) came together. In 2020, hiring managers were debating the highest-paying positions and talents in the IT/Computer Science/Engineering/Data Science sector.

To make the course more interactive, we've included a live code example in which we show you how each concept/principle may be used [step by step instruction]. Every step is thoroughly explained. "While artificial intelligence (AI) is a wide discipline that aims to emulate human abilities, machine learning is a subset of AI that focuses on learning from data."

Requirements:

• A computer with internet connection
  
• Passion & commitment

Who this course is for:

• Any student in college who wants to start a career in Data Science, Data mining, Machine Learning
  
• Any data analysts who want to level up in Machine Learning
  
• Anyone who is not satisfied with their job and who wants to become a Data Scientist
  
• Anyone who wants to create added value to their business by using powerful Machine Learning tools
  
• For anyone who does not have prior knowledge on programming. They have comprehensive chapters on python, Java programming, web development, Algorithms etc.

Subtitles:English
Udemy Rating: 4.3/5.0
Enroll here: https://www.udemy.com/course/professional-certificate-in-data-mining-machine-learning/

Are you interested in learning how to perform Data Mining like a pro? You've arrived to the right location. Welcome to Python's most fascinating Data Mining class. I'll show you the most effective algorithms for extracting significant insights that I've seen in my professional career.

It's easy to feel overwhelmed by so much data in the age of endless spreadsheets. This is when Data Mining comes into play. To quickly evaluate, detect trends, and provide you with a result. For me, the added benefit of Data Mining is that it allows you to stop number crunching and pivot table development, allowing you to focus on developing practical strategies based on the insights.

Requirements:

• Statistics - Linear and Logistic Regression
• Basic Python

Who this course is for:

• People looking to learn Data Mining algorithms

Subtitles: English
Udemy Rating: 4.2/5.0
Enroll here: https://www.udemy.com/course/data-mining-python/

This is a "hands-on" business analytics or data analytics course that teaches how to do dozens of data mining operations using real data and data mining cases using the popular, free R software. It covers important data analysis, data mining, and predictive analytics skills, as well as data exploration, data visualization, and data mining, using one of the most widely used business analytics software suites today.

The course is organized as a series of dozens of demonstrations of classification and predictive data mining tasks, such as building classification trees, building and training decision trees, using random forests, linear modeling, regression, generalized linear modeling, logistic regression, and a variety of cluster analysis techniques.

The course also teaches and demonstrates "best practices" for using R software, including how to install R and RStudio, the characteristics of basic data types and structures in R, and how to input data into a R session using the keyboard, user prompts, or importing files from a computer's hard drive. The course resources include the software, presentations, data, and R scripts used in the dozens of case-based demonstration video lectures, allowing students to "take them home" and apply them to their own unique data analysis and mining problems. Each course section also includes "hands-on" tasks to support the learning process.

The course is aimed for undergraduate and graduate students who want to learn useful data analytics skills, as well as practicing predictive analytics experts who want to broaden their knowledge and capabilities in data analysis and data mining.

Requirements:

• Download and install no-cost R software (complete, easy-to-follow instructions are provided).
• Download and install no-cost RStudio IDE software (complete, easy-to-follow instructions are provided).

Who this course is for:

• Anyone who wants to learn more about performing data analysis using a variety of popular, contemporary data mining techniques.
  
• Data Mining beginners and professionals who wish to enhance their data mining knowledge and skill levels
  
• Individuals seeking to gain more proficiency using the popular R and RStudio software suites.
  
• Undergraduate students seeking to acquire in-demand analytics skills to enhance employment opportunities.
  
• Graduate students seeking to acquire a wider repertoire of analytics skills for research data analysis tasks.

Subtitles:English
Udemy Rating: 4.5/5.0
Enroll here: https://www.udemy.com/course/data-mining-with-r-go-from-beginner-to-advanced/

Scraping data from the internet is known as data scraping. Data scraping is a technique for obtaining information from many websites and APIs. This also entails automating online flows for data extraction from various web pages.

The 'Data Scraping and Data Mining from Beginner to Professional' course is designed to cover the themes that lead to the development of the most in-demand employment skills. These topics will assist you in comprehending Python principles and approaches.

This course is intended for complete novices. Learners devote enough time to have a good foundation. Then, gradually, learners will go much deeper with a lot of practical implementations, with each step discussed in detail.

You will progress at a steady pace because this course is simply a compendium of all the fundamentals. More than what you've learnt will be experienced. Instructors will assign you Home Work/assignments/activities/quizzes with solutions at the end of each concept. Based on the prior data scraping and data mining principles and approaches, they will examine / (further build) your learning. The majority of these exercises are intended to get you started with implementations.

Requirements:

• Basic understanding of HTML tags.
  
• Familiarity with Python.
  
• No prior knowledge of data scraping is needed. You start right from the basics and then gradually build your knowledge of the subject.
  
• A willingness to learn and practice.
  
• Since they teach by practical implementations, practice is a must thing to do.

Who this course is for:

• People who are quite beginners and know absolutely nothing about Data Scraping.
  
• People who want to make smart solutions.
  
• People who want to learn Data Scraping with real data.
  
• People who love to learn theory and then implement it using Python.
  
• People who want to learn Data Scraping along with its implementation in realistic projects.
  
• Data Scientists.
  
• Machine learning experts.
  
• Drop Shippers.

Subtitles:English, French, German, Portuguese, Spanish
Udemy Rating: 4.3/5.0
Enroll here:https://www.udemy.com/course/data-scraping-data-mining-from-beginner-to-pro-with-python/