Short Courses

Short Course 1

Data Analytics with Machine Learning


Dr. Manjunath Ramachandra, Wipro Technologies, Bangalore


Data analytics is an integral part of an organization spanning the collection, processing and rendering of the results. The processing of data involves a good number of algorithms. It encompasses pattern recognition in the data, clustering & classification, association of the data etc. If the data size is too large, it calls for a systematic break up, processing and then fusion of the results. This step involves big data analytics, making use of machine learning paradigms. The processed data is to be carefully analyzed and linked to the problem in hand, before rendering to the end user.

A new wave of tools and techniques are coming up to address the data analytics in the industry, considering and exploiting the ever increasing data size. They predominantly make use of machine learning algorithms.

Machine learning algorithms provide the required intelligence to handle the same in the constrained time, providing meaningful inferences.The course is wound around the machine learning algorithms for data processing.

The short course spans interactive session with intermittent discussions. Numerous examples and case studies will be provided.The planned contents look as below:

1. Overview of data analytics: It spans the life cycle of data consumption including cleansing, processing, interpretation & rendering. The limitations of conventional approaches would be highlighted.
2. Migration to Machine learning: This part explains the appropriateness of Machinelearning for data churning through various tools, techniques and algorithms.
3. Clustering: Clustering of data based on a variety of parameters such as statistical, physical, application etc. is an important step to find patterns in the data and subsequent classification.Different data clustering algorithms would be introduced with examples
4. Classification: Once the clustering model is ready, the new data emanating would fit in to one of the clusters through classification algorithms.
5. Association: Association of the data in to one of the known patterns is challenging and the same would be discussed in detail with examples.
6. Big data analytics: Quite often, the quantum of data required to be processed in an organization required cloud infrastructure for processing calling for fragmentation of the data before, parallelization of processing and merging of the results for inference and rendering. The different steps involved in this process would be explained

Relevance of the topic
Today, industry is facing the problem of handling large data sets and extracting the meaning from the same. The techniques being used are getting outdated and require the skilled hands to understand the results, bringing in a lot of subjectivity. Towards this end, software programs are being trained to understand the data, process the same and interpret the results more consistently. This is achieved by applying machine learning techniques for data churning.

This course is expected to be useful for both academic and industrial community. For faculty and the students, it provides a good understanding of the data analytics problem faced in the industry and the mechanism to address the same, throwing open an opportunity to readily get in to the various projects going on in this domain. It provides crucial link between data analytics and machine learning. Applied machine learning is the main feature of this course. The practitioners from the industry would find it interesting to address the live problems with multiple tools and techniques.


Dr. Manjunath Ramachandra is working at CTO office of Wipro Technologies, Bangalore as Principal consultant. He has a mixture of industrial and academic work experience for over twenty years in various fields of communication systems. His doctoral research spans signal processing, Communication networks and data transfer over the network and data integration. He has published about 140 papers in international conferences and journals and a book. He represented the organization in international standardization bodies such as Wi-Fi Alliance, served as the editor for the regional profiles standard in Digital living network alliance (DLNA) and as the industrial liaison officer for the CE-Linux Forum. He has chaired several international conferences and workshops. His research interests include signal processing applications for networking. He has worked as senior faculty, visiting professor and advisor for various institutions of Visveswaraiah technological university. He is reachable over +91 9740098984 with email manjunath.iyer@wipro.com

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