- Industry-relevant curriculum, delivered online or on-site lectures.
- Extensive use of Cloud-based virtual labs and Remote labs to give hands-on access to tools and platforms such as Jenkins, Docker, GitHub, SonarQube, Selenium, Tomcat, Maven, Open Project, Gantt Project and WireShark, Java, Python, Prolog, Lisp, Selenium Web driver, Python Ecosystem – NumPy, SciPy, Pandas, scikit-learn, MatplotLib; Searborn, Keras, NLTK, SQLite and pgmpy, Eclipse, Weka, Microsoft Power BI, TensorFlow, Tableau and Anaconda Navigator, EdgecloudSim and IoTSimEdge, Apache Hadoop, Apache Storm, Apache Spark, Apache Kafka, MongoDB, CockroachDB and MPI.
- The dissertation or project work in the final semester allows students to apply concepts and techniques learned during the programme to real-world situations.
- The programme entails a Continuous Evaluation System that assesses the learners, over convenient and regular intervals. Such a system provides timely and frequent feedbacks and helps busy working professionals to stay on track with the programme.
- The education delivery methodology is a blend of classroom and experiential learning. Experiential learning consists of lab exercises, assignments, case studies and work-integrated activities.
- Participants who successfully complete the programme will become members of the prestigious global community of BITS Pilani Alumni.
Classes are conducted by a pool of faculty members comprising of academicians from BITS Pilani, and guest faculty who are experienced industry professionals.
Participants need to take at least 12 courses towards coursework, and complete one Project/ Dissertation. The coursework requirement for the programme would consist of a set of core courses and electives. Core courses are compulsory for all participants, while electives can be chosen based on individual learning preferences.
The programme offers a degree of customisation to address the specific L&D needs of your organisations.
- Software Architectures
- Cloud Computing
- Agile Software Processes
- Elective 1
- Software Product Management
- Software Testing Methodologies
- Elective 2
- Elective 3
- Elective 4
- Elective 5
- Elective 6
- Elective 7
- Data Visualization
- Data Mining
- Artificial Intelligence
- Object Oriented Analysis and Design
- Introduction to DevOps
- Data Warehousing
- Embedded System Design
- Database Design & Applications
- Data Structures & Algorithm Design
- Big Data Systems
- Cyber Physical Systems
- Service Oriented Computing
- Usability Engineering
- Secure Software Engineer
- Applied Machine Learning
- Blockchain Technologies & Systems
- Scalable Services
- Cross Platform Application Development
- Edge Computing
- Open Source Software Engineering
- Middleware Technologies
- Software Project Managemen
- Hardware Software Co-Design
- Software Quality Management
- Cyber Security
LECTURES DELIVERED ONLINE AND ONSITE
Lectures are delivered by BITS Pilani faculty members through live via online classes, or at the organisation's premises, and are designed to offer similar levels of interactivity as regular classrooms at the BITS Pilani campus.
Learners can access engaging learning material at their own pace which includes recorded lectures from BITS Pilani faculty members, course handouts and recorded lab content where applicable.
Continuous Assessment includes graded Assignments/ Quizzes, Mid-semester exam, and Comprehensive Exam.
The programme emphasizes on Experiential Learning that allows learners to apply concepts learnt in the classroom in simulated, and real work situations. This is achieved through 3 lab setups. Apart from these, AWS is also extensively used for experiments on Scalable Services.
- Cloud based virtual lab hosts Dev-Ops tool chain, languages and programming platforms for Full Stack engineering and other simulators:
- Tools : Jenkins, Docker, GitHub, SonarQube, Selenium, Tomcat, Maven, Open Project, Gantt Project and WireShark
- Languages and Library: Java, Python, Prolog, Lisp, Selenium Web driver, Python Ecosystem – NumPy, SciPy, Pandas, scikit-learn, MatplotLib; Searborn, Keras, NLTK, SQLite and pgmpy
- Programming Platforms: Eclipse, Weka, Microsoft Power BI, TensorFlow, Tableau and Anaconda Navigator
- Simulators: EdgecloudSim and IoTSimEdge
- Remote Lab facility caters to the needs of resource intensive requirements of Big Data Analytics applications with the following platforms:
- Apache Hadoop
- Apache Storm
- Apache Spark
- Apache Kafka
- Remote Lab facility caters to the needs of Embedded Systems and supports the following:
- Hardware / Software tools: MultiCore STM32 microcontroller based development boards.
- Simulation tools: Tossim, Cheddar and Keil.
CASE STUDIES AND ASSIGNMENTS
Carefully chosen real-world cases & assignments are both discussed and used as problem-solving exercises during the programme.
DISSERTATION/ PROJECT WORK
The fourth semester offers an opportunity for learners to apply their knowledge gained during the programme to a real-world like complex project. The learner is expected to demonstrate understanding of vital principles learnt across semesters and their ability to successfully apply these concepts.
The minimum eligibility to apply: Employed professionals holding B. Tech., B.E, M.Sc., MCA, or equivalent in relevant disciplines with at least 60% aggregate marks and minimum one year of work experience after the completion of the degree in relevant domains.
If you are an IT professional in a technical role such as Software Developer, Test Engineer, Lead Engineer, Architect, or techno-managerial roles such as Product Manager and Project Manager, you should consider applying to the programme.