Data mining defines the process of figuring out meaningful and impactful models that eventually turns into efficient algorithms which help to create unknown patterns, relationships, and anomalies between large and complex datasets. Operating this modeling system gradually discovered the importance of automation that will both simplify the complex and lengthy process of business models and generate insights that will change the way of performance. This change in the configuration of the thinking process of a system or machine is preferred by data mining service companies to bring out a brand's vision and value. Thus machine learning makes a system think when a query is entered, analyze and respond accordingly.
This course deals with the details of this automation and machine learning system and helps you to gain advanced knowledge of data mining. You will develop a strong foundation and profound understanding of data mining techniques that use industry-standard machine learning models and algorithms. The course will also take you through each machine learning model in great detail to help you attain the breakthrough skills of data mining in a real-world context through practicing a range of datasets in multiple projects.
To begin, enroll in the Specialization and choose the one you'd like to start with. When you subscribe to a course that is part of a Specialization. It’s okay to complete just one course — you can pause your learning or end your subscription at any time.
You'll need to successfully finish the all modules / articles / hands-on Project to complete the Specialization and earn your certificate
When you finish this course and complete the hands-on project, you'll earn a Certificate that you can share with prospective employers and your professional network.
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Note: Prime Courses is a learner-supported platform. When you buy through links on our site, we may earn an affiliate commission.With the rapid development of automated systems and the vast availability of data, it has become necessary for data scientists to have profound knowledge of various fast-pacing algorithms and models.
Aspiring data scientists with a good background in programming languages such as R and Python, statistics, and an understanding of machine learning algorithms and models will have a greater advantage. The average salary of a data scientist is around $117k per year.
In today's era of large datasets, it is highly important to incorporate automation to have control while analyzing and visualizing data. Machine learning is that part of artificial intelligence that helps to achieve this goal with valuable output, especially in data mining services. It has immensely impacted the functionalities of a machine in terms of recognizing and analyzing relations, anomalies, infographics, and videos and achieved a super-fast computer vision.
As said by the Head of AI at Google, Jeff Dean, the amount of error has been reduced from 3% in 2016 to that of 26% back in 2011. This shows the importance of machine learning algorithms in data mining. Moreover, according to Gartner, there will be 2.3 million job opportunities in the field of machine learning and a significant amount of these will also be available for data analysts. Hence, with the huge scope of the future job market, data mining skills with machine learning will help to cut down the competitiveness and achieve your dream career goals.
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