Admission Enquiry

With a surge of job opportunities in the fields of Artificial intelligence and Machine Learning, the world is indeed standing on the threshold of massive transformation.

According to the World Economic Forum's Future of Jobs Report, 85 million jobs will be replaced by machines with AI by 2025. While that might make you uneasy, the same report states that 97 million new jobs will be created by 2025 due to AI. Are you prepared? 

Prepare for a career with infinite possibilities in AI and ML with India’s most comprehensive and world-class M.Tech. Artificial Intelligence and Machine Learning programme without taking any career break.

This four-semester programme covers a wide variety of skills and knowledge areas, and enables IT professionals and Software developers to build a skill set that enables career elevation in some of the most sought-after job roles such as ML Engineers and AI Scientists, etc.

Option to pay fees using easy EMI with 0% interest and 0 down payment.

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Admission Enquiry

Please fill the below fields for fee details, programme information, and application instructions



Student Speak

  • Programme Highlights
  • Programme Curriculum
  • Mode of Learning
  • Eligibility
  • Fee Structure
  • How to Apply
  • Mode of Examination

Programme Highlights

  • The M.Tech. Artificial intelligence and machine learning is a Work Integrated Learning Programme (WILP) spanning four semesters. BITS Pilani's Work Integrated Learning Programmes are approved by the University Grants Commission (UGC).
  • Attend live-lectures from anywhere over an online technology-enabled platform. These live lectures would be conducted by faculty mostly on weekends or after business hours enabling working professionals to pursue the programme along with their jobs.
  • Offers the most comprehensive AI & ML Curriculum for working professionals.
  • The programme has an unmatched range & depth, and covers the widest variety of skill & knowledge areas required to develop advanced AI solutions.
  • Meant for IT professionals and Software developers aiming to become expert Machine Learning Engineers & AI Scientists.
  • The programme offers a set of core courses and elective courses, allowing students to gain expertise in Advanced Deep learning, Computational Learning theory, Speech Processing, Natural Language Processing, etc..
  • The programme offers a set of core courses and elective courses, allowing students to gain expertise in Advanced Deep learning, Natural Language Processing, etc.
  • 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 Virtual 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 .

Programme Curriculum

Semester-wise Pattern

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.

First Semester

  • Mathematical Foundations for Machine Learning.
  • Machine Learning
  • Introduction to Statistical Methods
  • Artificial and Computational Intelligence

Second Semester

  • Deep Neural Networks
  • Deep Reinforcement Learning
  • Elective 1
  • Elective 2

Third Semester

  • Elective 3
  • Elective 4
  • Elective 5
  • Elective 6

Fourth Semester

  • Dissertation

Electives

Pool of Electives for : Deep Learning Specialization

  • Advanced Deep learning #
  • Graph Neural Networks
  • ML System Optimization
  • Fair, Accountable, Transparent Machine Learning

Note: 3 courses are required including the course marked in #

Pool of Electives for : NLP Specialization

  • NLP Applications
  • Social Media Analytics
  • Natural Language Processing
  • Information Retrieval
  • Conversational AI

Note: 3 courses are required including the course marked in #

General Pool of Electives

  • MLOps
  • Design of Algorithms
  • Computer Vision
  • Probabilistic Graphical Models
  • Data Management for Machine Learning
  • Video Analytics
  • Advanced Data Mining
  • AI and ML techniques for Cyber Security

 

Mode of Learning

Mode of Learning

The Mode of Learning used in this programme is called - Work Integrated Learning. Internationally, Work Integrated Learning (WIL) is defined as "An educational approach involving three parties - the student, educational institution, and employer organization(s) - consisting of authentic work-focused experiences as an intentional component of the curriculum. Students learn through active engagement in purposeful work tasks, which enable the integration of theory with meaningful practice that is relevant to the students' discipline of study and/or professional development*.

An education model can be considered as WIL if and only if:

  1. The programs are designed and developed by the institute in collaboration with industry.
  2. Work-focused experiences form an active part of the curriculum.
  3. The program structure, pedagogy and assessment enable integration of theory-with relevant practice.

The innovative Work Integrated Learning Programs (WILP) of BITS Pilani are quite aligned with the above definition and requirements. The programs are designed in collaboration with its industry partners, subject matter experts from industry and academia that enable the students to remain relevant in their chosen profession, grow in their career and retain the habit of lifelong learning. The continued availability of workplace related experiences along with the weekly instruction sessions promote integration of theory with practice. An active participation of the organization mentor in the learning process of the student plays a key role. Case studies, simulation exercises, labs and projects further strengthen this integration.

The WILP of BITS Pilani is comparable to its campus-based programs in terms of structure, rigor, instruction, labs, assessment, faculty profile and learning support. The pervasive adoption of technology in all its academic processes makes the same high-quality education of BITS Pilani available to the aspirants at scale with the required flexibility. 

Key Benefits of BITS Pilani WILP

1) Can pursue the programme without any career break and along with the job.

2) The programme curriculum is highly relevant to sectors, industries and organisations they work for

3) In addition to the institute, the learning experience of working professionals in the programme is also supported by the employer organisation and Industry Mentors.

4) Effective use of technology to deliver a range of learning interventions at the location of the working professional such as faculty contact sessions, asynchronous learning materials, remote, virtual and cloud labs, Learner support, peer to peer collaboration etc. 

5) Contact sessions with faculty take place mostly over weekends or after business hours and are conducted over a technology platform that can be accessed from anywhere. 

6) Mid semester and End semester examinations for every semester are conducted mostly at designated examination centres distributed across the country (for details refer to link mode of examinations) 

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

EXPERIENTIAL 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. Tensorflow for Deep Learning and various Python libraries for data processing, machine learning, OpenCV for computer vision, NLTK for NLP etc.
CONTINUOUS ASSESSMENT

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

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.

Eligibility

  1. Employed professionals holding B.E. / B.Tech. with at least 60% aggregate marks and minimum one-year relevant work experience after the completion of the degree are eligible to apply.
  2. Employed professionals holding MCA / M.Sc. or equivalent with at least 60% aggregate marks with university level mathematics / statistics as mandatory subjects and minimum one-year relevant work experience after the completion of the degree are also eligible to apply.
  3. Working knowledge of Computing and programming is required.

Fee Structure

For fee details, programme information and application instructions, please click here to download the Programme Brochure.

How to Apply

For application instructions, programme information and fee structure, please click here to download the Programme Brochure

Mode of Examination

Mode Of Examination

Mode of Examinations applicable for students admitted in Batch starting in Oct/Nov 2024:

Semester 1, 2 and 3 have Mid-Semester Examinations and Comprehensive Examinations for each course. These examinations are mostly scheduled on Friday, Saturday or Sunday. Students need to appear in person for taking the examinations at the institution’s designated examination centres as per the examination schedule, Instructions, rules and guidelines announced before every examination. 

For Indian Students:

Students can take their examination at any of our 33 designated examination centres in India at the following locations:

  1. South Zone: Bangalore - North, Bangalore - Central, Bangalore - South, Bangalore - East, Chennai - North, Chennai - Central, Chennai - South, Hyderabad, Secunderabad, Vijayawada, Visakhapatnam, Kochi, Thiruvananthapuram and Coimbatore.
  2. North Zone: Delhi, Gurugram, Noida, Jaipur, Chandigarh, Lucknow and Pilani.
  3. West Zone: Mumbai, Navi-Mumbai, Pune, Pune - Pimpri Chinchwad, Goa, Ahmedabad, Indore and Nagpur.
  4. East Zone: Kolkata, Bhubaneswar, Guwahati and Jamshedpur.

For International Students: 

  • In addition to the above locations, the institution also has a designated international examination centre, located in Dubai.
  • To facilitate the learning of international students, applying from any other location except India and Dubai, the mode of examinations will be online, which can be availed by meeting the requirements of the institute.
  • To know more about the requirements for online examinations, Click here
  • Indian students, who are temporarily based out of India, can also avail of online examinations on request by meeting the above-mentioned requirements of the institute.

Classes begin from November 23rd.

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