Description

About the course

This course covers in details, the fundamentals of Data Mining, and basic algorithms like Data Processing, Association Rule Mining, Classification Basics, Decision Tree, Bayes Classifier, K nearest neighbor. Then it covers Support Vector Machine, Kernel Machine. After that, it covers Clustering, Outlier Detection, and Sequence Mining. In addition to this, it covers Evaluation, Visualization and the implementations in open source software. Finally, the course concludes with the demonstrations of case studies on industrial problems. This is completely an online course, and you can access it from anywhere in the world.

Learning Outcomes

After completing this course, you will be able to:

• Demonstrate advanced knowledge of data mining concepts and techniques.
• Apply the techniques of clustering, classification, association finding, feature selection in the visualization of real-world data.
• Set up a Data Mining process for an application, including data preparation, modeling, and evaluation.
• Boost your hireability through innovative and independent learning.

Target Audience

The course can be taken by:

Students: All students who are pursuing any technical/professional courses in IT / Data Science.

Teachers/Faculties: All teachers/faculties who wish to acquire new skills or improve their efficiency in Data Science.

Professionals: All working professionals, who wish to enhance their skills by learning data mining techniques.

Why Learn Data Mining?

Modern businesses are complex and rely on data. This means that the amount of data has increased. Data Mining has great importance in today’s highly competitive business environment. Data Science has gained unprecedented traction in the job market, as Big Data, Data Analytics, Data Mining, and Machine Learning become more relevant to the mainstream IT industry. Around the world, organizations are fiercely fighting with each other for skilled data professionals available in the market. As a result, the financial packages for different data science roles are consistently going into overdrive. An estimated 2.7 million job postings for Data Analytics and Science are projected by 2020.

Course Features

• 24X7 Access: You can view lectures as per your own convenience.
• Online lectures: 19 hours of online lectures with high-quality videos
• Updated Quality content: Content is latest and gets updated regularly to meet the current industry demands.

Test & Evaluation

1. During the program, the participants will have to take all the assignments given to them for better learning.

2. At the end of the program, a final assessment will be conducted.

Certification

1. All successful participants will be provided with a certificate of completion.

2. Students who do not complete the course / leave it midway will not be awarded any certificate.