International School of Engineering Madhapur, Hyderabad, Telangana

Real-world, Challenging Projects Every student works on a real-world, advanced data science project. View current projects here. Rigorous Coursework The course is fast paced to suit the needs of students, working professionals and employers. Each week, students spend 16 hours in the classroom and 12 hours (optional) in mentor-driven recitation sessions. Most students spend another 20-40 hours on self-study, assignments, quizzes and project work. In-Demand Industry Skills Imparted - Programming Expertise: R, Hadoop and its Ecosystem, exposure to SAS andor SPSS - Topical Expertise: Statistical Modeling, Data Analytics, Machine Learning, Text Mining and Optimization - Techniques: Regression, Time Series, Decision Trees, Clustering, Association Rules, K-Nearest Neighbors, Neural Nets, SVM, Genetic Algorithms, Monte Carlo Simulations, Linear Programming, Quadratic Programming, etc.

Most Indian Masters programs are purely academic and offer no value to a practicing engineer for getting ahead in the career. To bridge this gap, ISE and GITAM University have designed the Executive Masters program from scratch, with inputs from industry experts, to transform a generalist to a specialistconsultant. The degree is titled “M.Tech. in Applied Computer Science and Technology” and will be awarded by the GITAM University. Our first focus area is “Business Analytics and Optimization“. In due course, executive M.Tech. with a variety of specializations will be launched. Analytics is one of the fastest growing and highly in-demand field that offers its practitioners eligibility in over 50 different types of jobs with salaries that rival the best engineering and management jobs.

We provide the follow modules in CPAE: 1. Essentials of Applied Predictive Analytics 2. Statistical Modeling for Predictive Analytics in Engineering and Business 3. Effective Decision Making: Optimization, Simulation and Statistical Methods 4. Engineering Big Data with R and Hadoop Ecosystem 5. Methods and Algorithms in Machine Learning 6. Text Mining and Social Media Analytics 7. Advanced Topics in Machine Learning 8. Architecting Data Analytics Solutions in the Real World

Programs: 1. Essentials of Applied Predictive Analytics 2. Engineering Big Data with R and Hadoop Ecosystem