What is Data Mining?
Big Data!!! Are you demotivated when your peers are discussing about data science and recent advances in Big Data? Did you ever think how Flipkart and Amazon are suggesting products for their customers? Do you know how financial institutions/retailers are using Big Data to transform themselves into next-generation enterprises? Do you want to be part of the world class next generation organizations to change the game rules of the strategy making and to zoom your career to newer heights?
Here is the power of Data Science in the form of Data Mining concepts which are considered most powerful techniques in Big Data Analytics.
Data Mining with R unveils underlying amazing patterns, wonderful insights which go unnoticed otherwise, from the large amounts of data. Data mining tools predict behaviours and future trends, allowing businesses to make proactive, unbiased and scientific-driven decisions. Data mining has powerful tools and techniques that answer business questions in a scientific manner, which traditional methods cannot answer. Adoption of data mining concepts in decision making changed the companies, the way they operate the business and improved revenues significantly.
Companies in a wide range of industries such as Information Technology, Retail, Telecommunication, Oil and Gas, Finance, Healthcare are already using data mining tools and techniques to take advantage of historical data and to create their future business strategies.
Data mining can be broadly categorized into two branches i.e. supervised learning and unsupervised learning. Unsupervised learning deals with identifying significant facts, relationships, hidden patterns, trends and anomalies. Clustering, Principle Component Analysis, Association Rules, etc., are considered unsupervised learning. Supervised learning deals with prediction and classification of the data with machine learning algorithms. Weka is the most popular tool for supervised learning.
Things You Will Learn
- Basic matrix algebra
- Introduction to data mining
- Dimension reduction techniques: Principal Component Analysis(PCA)
- Singular Value Decomposition (SVD)
- Association rules
- Sequential pattern mining
- Recommender Systems (Collaborative Filtering)
- Network Analytics: Degree centrality, Closeness Centrality etc.
- Cluster Analysis- Application on segmentation, anomaly detection
- Hierarchical clustering and K-means clustering with various distance measures and for continuous/ categorical variables
- Overview of machine learning/supervised learning
- Data exploration methods: Understanding data(distributions, visualizations), Data nuances, data transformations
- Basic classification algorithms
- Version spaces and decision trees classifier
- K-Nearest Neighbors and Parzen window
- Bayesian classifiers: naïve Bayes and other discriminant classifiers
- Perceptron and Logistic regression
- Neural networks
- Advanced classification algorithms
- Bayesian Networks
- Support Vector Machines
- Model validation and interpretation
- Multi-class classification problem
- Bagging(random forest) and Boosting( Gradient Boosted Decision Trees)
- Regression Analysis
- Recommendation engines
- Information retrieval
- Practical tips in modeling: Bias vs trade-off, Feature engineering and incorporating domain knowledge.
360DigiTMG is a training and consulting firm with its global headquarters in Houston, Texas, USA. Alongside to catering to the tailored needs of students, professionals, corporates and educational institutions across multiple locations, 360DigiTMG opened its offices in multiple strategic locations such as Australia, Malaysia for the ASEAN market, Canada, UK, Romania taking into account the Eastern Europe and South Africa. In addition to these offices, 360DigiTMG believes in building and nurturing future entrepreneurs through its Franchise verticals and hence has awarded in excess of 30 franchises across the globe. This ensures that our quality education and related services reach out to all corners of the world. Furthermore, this resonates with our global strategy of catering to the needs of bridging the gap between the industry and academia globally.
- Instructor-led online training is an interactive mode of training where you and the trainer will log in at the same time and live sessions will be done virtually. These sessions will provide scope for active interaction between you and the trainer.
- 360DigiTMG offers a blended model of learning. In this model, you can attend classroom, instructor-led live online and e-learning (recorded sessions) with a single enrolment. A combination of these 3 will produce a synergistic impact on the learning. You can attend multiple Instructor-led live online sessions for one year from different trainers at no additional cost with the all new and exclusive JUMBO PASS.
- It is a live instructor-led interactive session which is done at a specific time where you and the trainer will log in at the same time. The same session will be also recorded and access will be provided to revise, recap or watch any missed session.
- Not a problem even if you miss a live Data Mining session for some reason. Every session will be recorded and access will be given to all the videos on 360DigiTMG’s state-of-the-art Learning Management System (LMS). You can watch the recorded Data Mining sessions at your own pace and convenience.
- Yes, after successfully completing the course you will be awarded a course completion certificate from 360DigiTMG.
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