Executive M.Tech. in Data Science
The department of Computer Science and Engineering at IIT Hyderabad is launching a new M.Tech. program, Executive M.Tech. in Data Science, exclusively for industry professionals from next academic year (i.e., August 2015). The program is self-paced so that candidates can have flexibility in completing the program in 2-4 years. It can be taken at IITH campus or remotely through video enabled online courses.Nonetheless, periodic visits to IITH, possibly on weekends, may be required.
Executive M.Tech in Data Science Brochure
THE NEED FOR EXECUTIVE M.TECH IN DATA SCIENCE PROGRAM
There are many applications, such as social media, healthcare, e-commerce, weather forecast, traffic monitoring, etc., that are producing massive amounts of data, the so-called “BIG DATA”, with Volume, Velocity, Variety, Veracity and Value (the five “Vs” of Big Data challenges) at an unprecedented scale. This has led to a critical need for skilled professionals, popularly known as Data Scientists, who can mine and interpret the data. Making sense of this massive data is a very difficult challenge for scientific, technological and industrial disciplines. Unfortunately, there is a gap between the demand and supply of data scientists and technologists. Following are the chief reasons behind this gap:
- Undergraduate courses are too generic for addressing issues in this area in a focused manner.
- There aren’t many postgraduate courses that focus explicitly on Data Science.
- Even if some generic postgraduate programs can be tailored to focus on Data Science through electives, professionals working in the industry or Research and Development establishments do not have the luxury of taking two years off for pursuing higher studies.
With these factors in mind, the CSE Department at IIT Hyderabad proposes a two-year course-work based M.Tech. program in Data Science area that is flexible and can be self-paced. This
program is exclusively designed to cater to the needs of working individuals, wherein a candidate is expected to do twelve 2-credit courses over a period of 2-4 years. Ideally, one can take 3 courses per semester. The classes will be held over the weekends (or other timings suitable for working professionals) with each class having a 3-hour duration. More details can be seen in this brochure
Data Science Workflow
Above figure shows the workflow of a data scientist, which can be broken down to following four essential steps:
- Data Collection: Proliferation of smart devices, sensors, web, mobile and social media has led to explosive amount of complex data. To make use of this data, one needs expertise in Computer Networks and Databases to effectively collect and manage such huge volumes of data.
- Data Processing: The next step is to convert the raw data into forms that can be scientifically analyzed, which includes data cleaning and transformation. For example, by transforming social network data into graph data, one can use concepts from Graph Theory to analyze social network data. To process huge volumes of data, one needs expertise in Databases and High Performance Computing. The data one needs to handle is a heterogeneous mix of different types of data, such as images, videos, text, social networks, etc. To handle these different types of data one needs expertise in areas such as Image and Video Analytics, Information Retrieval, Social Media Analytics, etc.
- Data Analysis: The third step is to analyze the processed data using various Statistical,Data Mining and Machine Learning algorithms. Most of the existing data analysis algorithms do not scale to large datasets. As a result, one needs expertise in Statistics, Data Mining and High Performance Computing to design systems that can efficiently analyze large volumes of complex data.
- Data Product: The final step is to make decisions from the data analysis and also deliver the analyzed information to the world in the form of various data products. This is often done using data visualization techniques, which are integrated with various smart devices. This step requires expertise in Information Visualization, Databases and Computer Networks.
From the above workflow, it can be understood that the task of a data scientist is quite complex and it requires expertise in multiple sub-disciplines of computer science and engineering. Through the Executive M.Tech. program in Data Science, our goal is to provide high-quality training in the aforementioned areas to meet the growing demands of the market for data scientists and technologists, and to serve our nation’s economy from our capacity as an institution of national importance.