M.Tech. Programmes

DEGREE PROGRAMMES Join the league of Digital Tech specialists

Join the league of Digital Tech specialists

With specialization in Data Analytics, Internet of Things, Embedded Systems, Security, Networks and Cloud

New-age digital technologies are transforming the world and spawning a massive demand for specialists in areas like Data Analytics, IoT, Embedded Systems, Security, Networks and Cloud, etc. While specialists in Data Analytics are powering organisations with transformative capacities to win in their businesses, the IoT and Embedded Systems specialists are revolutionising our lives and society. Massive growth in connectivity means a greater need for security specialists and huge connected infrastructure needs specialists in Network and Cloud.

M.Tech. Software Systems is a unique programme that enables working professionals to specialise in many new-age technology areas and be ready to transition into high demand careers. The programme enables the learners to specialize in some of the fastest-growing domains like Data Analytics, Internet of Things, Embedded Systems, Security, Networks and Cloud. A comprehensive curriculum, extensive emphasis on experiential learning using remote labs and cloud labs and a flexible education methodology that enables working professionals to acquire a prestigious post-graduate engineering degree while pursuing their careers, the M.Tech. Software Systems is just the right programme for career growth in the software industry.

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  • Programme Highlights
  • UGC Approval
  • Programme Curriculum
  • Learning Methodology
  • Eligibility Criteria
  • Fee Structure
  • How to Apply
Programme Highlights
  • M.Tech. Software Systems is a BITS Pilani Work Integrated Learning Programme (WILP). BITS Pilani Work Integrated Learning Programmes are UGC approved.

  • The programme is of four semesters, with online classes conducted mostly on weekends or after business hours. You can pursue the programme without any career break.

  • The programme offers a set of core courses and elective courses, allowing students to specialize in Data Analytics, Internet of Things, Embedded Systems, Security, Networks and Cloud.

  • The programme makes use of Languages, Platforms, and Libraries. These include NS2, Net-SNMP, WireSha, R, Python, Prolog, Lisp, RStudio, Weka, Microsoft Power BI, TensorFlow, Anaconda Navigator, Python Ecosystem – NumPy, SciPi, Pandas, scikit-learn, MatplotLib; Searborn, Keras, NLTK, pgmpy etc., Keil, CCS Studio, Tossim, Cheddar, Jenkins, GitHub, SonarQube, Selenium, Tomcat, Maven, Java, Eclipse, Code::Blocks, Android Studio, Jupyter Notebooks, Spyder, Multisim, CPU-OS Simulator, SQLite, MATLAB, , Gantt Project, Open Project and XAMPP.

  • The Dissertation (Project Work) in the final semester enables students to apply concepts and techniques learned during the programme.

  • The programme uses a Continuous Evaluation System that assesses the learners over convenient and regular intervals. Such a system provides timely and frequent feedback and helps busy working professionals stay on course 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 an elite & global community of BITS Pilani Alumni

  • Option to submit fee using easy-EMI with 0% interest and 0 down payment

Classes are conducted by a pool of faculty members comprising of academicians from BITS Pilani, and guest faculty who are experienced industry professionals.

UGC Approval

BITS Pilani is an Institution of Eminence under UGC (Institution of Eminence Deemed to be Universities) Regulations, 2017. The Work Integrated Learning Programmes (WILP) of BITS Pilani constitutes a unique set of educational offerings for working professionals. WILP are an extension of programmes offered at the BITS Pilani Campuses and are comparable to our regular programmes both in terms of unit/credit requirements as well as academic rigour. In addition, it capitalises and further builds on practical experience of students through high degree of integration, which results not only in upgradation of knowledge, but also in up skilling, and productivity increase. The programme may lead to award of degree, diploma, and certificate in science, technology/engineering, management, and humanities and social sciences. On the recommendation of the Empowered Expert Committee, UGC in its 548th Meeting held on 09.09.20 has approved the continued offering of BITS Pilani’s Work Integrated Learning programmes.

Programme Curriculum

The programme offers specialisations in high-demand areas such as Data Analytics, Internet of Things, Embedded Systems, Security, Networks and Cloud.

First Semester

  • Data Structures & Algorithms Design

  • Database Design & Applications

  • Distributed Computing

  • Elective 1

Second Semester

  • Software Architectures

  • Elective 2

  • Elective 3

  • Elective 4

Third Semester

  • Elective 5

  • Elective 6

  • Elective 7

  • Elective 8

Fourth Semester

  • Dissertation


  • Artificial Intelligence

  • Computer Organization and Software Systems

  • Distributed Data Systems

  • Software Engineering and Management

  • Usability Engineering

  • Object-oriented Analysis & Design


Specialisation in Data Analytics

Participants who earn a specialisation in Data Analytics will learn how to apply principles behind modern Data Analytics techniques; apply statistical and machine learning methods to real data; evaluate their performance and effectively communicate the results; and build expertise in advanced Artificial Intelligence topics such as Deep Learning and Natural Language Processing

Pool of Electives

  • Advanced Statistical Techniques for Analytics

  • Applied Machine Learning

  • Metaheuristics for Optimization

  • Data Mining

  • Data Warehousing

  • Deep Learning

  • Information Retrieval

  • Mathematical Foundations For Data Science (Mandatory Course for Specialization)

  • Natural Language Processing

Specialisation in Internet of Things

Participants will build expertise in the building blocks of IoT technology and explore the vast spectrum of IoT applications; assess, select and customize technologies for IoT applications; connect the cyber world with the physical world of humans, automobiles and factories; integrate geographically distributed devices with diverse capabilities; design and implement IoT applications that manage big data

Pool of Electives

  • Embedded Systems Design (Mandatory Course for Specialization)

  • Cyber Physical Systems (Mandatory Course for Specialization)

  • Networked Embedded Applications

  • Cross Platform Application Development

  • Cloud Computing

  • Data Management for IoT

  • Stream Processing and Analytics

  • Embedded Network Security

Specialisation in Networks and Cloud

Participants will build expertise in how to design, and manage software and hardware that control digital networks; conceptualize and solve engineering problems concerning wireless and mobile networks effectively and arrive at the feasible optimal solution, individually and in teams; master formal techniques for network analysis, design and operate data centers; Network Security aspects, Storage Area Networks, Virtualizations, and Cloud Computing Concepts which have great scope and opportunities in the industry; apply advanced software engineering techniques (e.g., software-defined networks, containerization, etc.) to compute, improve and master the development of distributed networks.

Pool of Electives

  • Advanced Computer Networks

  • Cloud Computing (Mandatory Course for Specialization)

  • Computer Networks (Mandatory Course for Specialization)

  • Data Storage Technologies and Networks

  • Design and Operation of Data Centres

  • Edge Computing

  • Mobile Networks

  • Network Programming

  • Network Security

  • Software Defined Networks

  • Wireless and Mobile Communication

  • Middleware Technologies

Specialisation in Security

Participants will build expertise in the implementation of core software engineering principles and the best cybersecurity practices in terms of policies, models and mechanisms; gain knowledge about securing computer networks and systems; learn to examine secure software design and development practices in cybersecurity; understand the prevalent network and distributed system attacks; incorporate approaches for incident response and security risk management; understand the key concepts in domain-specific security.

Pool of Electives

  • Cyber Security (Mandatory Course for Specialization)

  • Cryptography

  • Network Security

  • Ethical Hacking

  • Identity and Access Management Technologies

  • Cyber Crimes, Forensics and Incident Handling

  • Cloud, IoT and Enterprise Security

  • Secure Software Engineering

  • Blockchain Technologies & Systems

  • AI and ML Techniques in Cybersecurity

Specialisation in Embedded Systems

Participants will gain expertise in key areas of Application (Domain) Specific System Design such as scope of a Processor (Embedded processors, Desktop systems, Servers, and Supercomputers), the target application (general-purpose versus domain-specific), the characteristics of the design objectives (Speed, Power consumption, Cost, Reliability, Availability, and Reconfigurability), and the measurement and analysis of resulting designs.

Pool of Electives

  • Embedded Middleware Design

  • Embedded System Design (Mandatory Course for Specialization)

  • Fault Tolerant Embedded System

  • Hardware Software Co-Design

  • Networked Embedded Applications

  • Parallel Embedded Architectures

  • Real Time Scheduling

  • Real Time Systems

  • Software for Embedded Systems

General Pool of Electives

  • Artificial Intelligence

  • Computer Organization and Software Systems

  • Distributed Data Systems

  • Software Engineering and Management

  • Usability Engineering

  • Object-oriented Analysis & Design

Electives can be chosen either from the General pool of electives or from across other pools of electives for Specialisations. Specialisations are optional. To earn a Specialization, a participant must select and successfully complete at least 5 courses from that Specialisation pool

For more information on programme curriculum download the programme brochure

Electives finally offered will be at the discretion of the BITS Pilani, and will be decided in consultation with HCL. Offered electives will be made available to enrolled students at the beginning of each semester.

Learning Methodology
Online lectures


  • Lectures are conducted live via online classes. These lectures can be attended via the internet using a computer from any location. These online classrooms offer similar levels of interactivity as regular classrooms at the BITS Pilani campus.

  • The class schedule is announced within 1 week of completion of the admission process.

  • The online lectures are conducted usually over weekends for a total of 7-8 hours per week. If you miss a lecture, you can also access the recorded lecture on the internet.

Digital Learning


Learners can access engaging learning material which includes recorded lectures from BITS Pilani faculty members, course handouts and recorded lab content where applicable.

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.

experimental Learning


The programme emphasises on Experiential Learning that allows learners to apply concepts learnt in the classroom in simulated, and real work situations. This is achieved through:

Simulation Tools, Platforms & Environments: Some or all of the following would be utilised across the programme.

  • Cloud based virtual lab which supports the following programming languages/tools/simulators:

    • Networks: NS2, Net-SNMP and WireShark

    • Data Analytics:

      • Languages: R, Python, Prolog and Lisp

      • Platforms: RStudio, Weka, Microsoft Power BI, TensorFlow and Anaconda Navigator

      • Libraries: Python Ecosystem – NumPy, SciPi, Pandas, scikit-learn, MatplotLib; Searborn, Keras, NLTK, pgmpy etc.

    • Embedded and IOT: Keil, CCS Studio, Tossim and Cheddar

    • Devops: Jenkins, GitHub, SonarQube, Selenium, Tomcat and Maven

    • Programming Environments: Java, Eclipse, Code::Blocks, Android Studio, Jupyter Notebooks and Spyder

    • Others: Multisim, CPU-OS Simulator, SQLite, MATLAB, , Gantt Project, Open Project and XAMPP

  • 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

    • MongoDB

    • CockroachDB

    • MPI

  • Remote Lab facility caters to the needs of Embedded Systems and IoT. It 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.

Continour Assessment


Continuous Assessment includes graded Assignments/ Quizzes, Mid-semester exam, and Comprehensive Exam.

Eligibility Criteria

Minimum eligibility to apply: Employed professionals holding B Tech., BE, M.Sc, MCA or equivalent in relevant disciplines with at least 60% aggregate marks and minimum 18 months of relevant work experience within HCL Technologies, are eligible to apply.

The above are only the minimum criteria to apply. The final decision to offer admission to an applicant rests with BITS Pilani which will be made based on an overall review of your application information.

It is strongly advised to refer and check HCL's policy details and other Eligibility Criteria of the programme before applying, as all fees are non-refundable.

Fee Structure
  • The following fees schedule is applicable for candidates seeking new admission during the academic year 2024-25

    Application Fees (one time) : INR 1,500

    Admission Fees (one time) : INR 16,500

    Semester Fees (per semester) : INR 66,750

  • The one-time Application Fee is to be paid at the time of submitting the Application Form through the Online Application Centre.

  • Admission Fee (one-time) and Semester Fee (for the First Semester) are to be paid together once admission is offered to the candidate. Thus, a candidate who has been offered admission will have to pay Rs. 84,750/-. You may choose to make the payment using Netbanking/ Debit Card/ Credit Card through the Online Application Centre.

  • Semester Fee for subsequent semesters will only be payable later, i.e. at the beginning of those respective semesters.

  • Any candidate who desires to discontinue from the programme after confirmation of admission & registration for the courses specified in the admit offer letter will forfeit the total amount of fees paid.

  • All the above fees are non-refundable.

How to Apply
  • Click here to visit the Online Application Center. Create your login at the Online Application Center by entering your official HCL Email ID only and create a password of your choice. Once your login has been created, you can anytime access the Online Application Center using your official email ID and password.

  • Begin by clicking on Step 1 - ‘Fill/ Edit and Submit Application Form’. This will enable you to select the programme of your choice. After you have chosen your programme, you will be asked to fill your details in an online form. You must fill all details and press ‘Submit’ button given at the bottom of the form.

  • Now, click on 'Pay Application Fee’ to pay INR 1,500/- using Netbanking/ Debit Card/ Credit Card

  • Finally, click on 'Upload & Submit All Required Documents’. This will allow you to upload one-by-one all the mandatory supporting documents such academic certificates and transcripts, photograph, etc. and complete the application process. Acceptable file formats for uploading these documents are .DOC, .DOCX, .PDF, .ZIP and .JPEG

  • Upon receipt of your Application Form and all other enclosures, the Admissions Cell will scrutinise them for completeness, accuracy and eligibility.

  • Admission Cell will intimate selected candidates by email within two weeks of submission of application with all supporting documents. The selection status can also be checked by logging in to the Online Application Centre.