M.Tech. Artificial Intelligence and Machine Learning

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.

Study without

Career Break

Easy EMI Option With

0% Interest & 0 down payment

Admission begins

August 2024

Fees per semester

INR 71,750

M.Tech. Artificial Intelligence and Machine Learning Video

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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, Natural Language Processing, etc.
The programme makes use of Tools and Technologies. These include Tensorflow for Deep Learning and various Python libraries for data processing, machine learning, OpenCV for computer vision, NLTK for NLP 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 .

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 11.09.20 has approved the continued offering of BITS Pilani’s Work Integrated Learning programmes.

Programme Curriculum

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.

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

Deep Neural Networks
Deep Reinforcement Learning
Elective 1
Elective 2

Elective 3
Elective 4
Elective 5
Elective 6

Dissertation

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

Note: Choice of Electives is made available to enrolled students at the beginning of each semester. Students' choice will be taken as one of the factors while deciding on the Electives offered. However, Electives finally offered will be at the discretion of the Institute

For detailed programme curriculum, download the brochure.

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Mode of Learning

The Mode of Learning is based on a powerful educational approach called Work Integrated Learning. For detailed description of work integrated learning Click here

The benefits of the Work Integrated Learning Mode are as follows:

1) It enables Working Professionals to pursue the programme without any career break and along with their jobs.

2) The programme curriculum is designed for high relevance to sectors, industries and organisations the students are presently employed in.

3) Learning experience design also endeavours to integrate support and value addition by the Industry Mentors and employer organizations.

4) Enables working professionals to attend live-lectures from anywhere over an online technology-enabled platform. For the benefit of working professionals these live lectures are conducted by faculty mostly on weekends or after business hours.

5) Leverages the latest educational technologies to provide easy access to asynchronous learning materials, Learner support services and peer to peer collaboration etc.

6) Great emphasis on experiential learning by providing access to state of the art remote labs, virtual labs and cloud labs and simulations as applicable to individual courses.

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.

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

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.

Industry Talks

The programme features Industry Talks on some of the most exciting developments, and pressing issues faced by businesses in the technology space. Speakers include business leaders, R&D professionals, and academicians from leading technology firms and institutions.

Some of the recent and upcoming sessions include:

Title of Tech Talk	Date	Speaker(s)
Illustrating Edge AI Techniques and Tools towards Digitally Transformed Cities	April 2023	Dr. Pethuru Raj, Chief Architect and VP, Edge AI Division, Reliance Jio Platforms
Blockchain as a key component of FinTech	January 2023	Raam Baranidharan, CTO - BlokTrek
Personalizing the Online Grocery Substitution Experience	February 2022	Dr. Rahul Ghosh, Senior Director of Data Science, Walmart India Kamiya Motwani, Senior Data Science Manager, Walmart India
Applying Data Science Technologies in HealthCare	December 2021	Manisha Mantri, Joint Director, C-DAC, Pune
Financial Risk Modelling using ML Techniques	November 2021	Mayank Rasu, Guest Faculty at WILP CSIS Department
Enterprise Cloud Transformation Journey	October 2021	Surendra Tipparaju, Principal Architect Manager, Microsoft Hyderabad
Cyber Threat Intelligence	June 2021	Nandi Dharma KishoRe H.N., Assistant Vice President - K7 Threat Control Lab
Cellular V2X	May 2021	Brijesh Unnikrishnan, Principal Engineer at Mavenir.
3D processing and Computation - An Engineering View	May 2021	Dr. Raghavendra Singh, Director, Computer Vision and Machine Learning at Oyla, Inc.
SDLC in the Devops world	April 2021	Meshach Samuel, Associate VP, HCL
Recent Trends in Database Administration	April, 2021	Gautam Avarsala Managing Director, dBPro Software Solutions
Service Assurance in 5G networks: An AI/ML perspective	March, 2021	Ashvin Lakshmikantha, Principal Engineer –System Architecture Anand Eswaran, Principal Engineer – System Architecture Cloud Networking Group, Ericsson R&D, Bangalore
Blockchain:Technology backbone for Digital economy	March, 2021	Sridhar Vedhanabatla Associate Director, Information Security & Privacy, Gainsight

Mode Of Examination

Mode of Examinations applicable for students admitted in Batch starting in April/May 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.

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

South Zone: Bangalore - North, Bangalore - Central, Bangalore - South, Bangalore - East, Chennai - North , Chennai - Central , Chennai - South, Hyderabad, Secunderabad, Vijayawada, Visakhapatnam, Kochi, Thiruvananthapuram and Coimbatore.

North Zone: Delhi, Gurugram, Noida, Jaipur, Chandigarh, Lucknow and Pilani.

West Zone: Mumbai, Navi-Mumbai,Pune, Pune - Pimpri Chinchwad, Goa, Ahmedabad, Indore and Nagpur.

East Zone: Kolkata, Guwahati, Jamshedpur and Bhubaneshwar.

In addition to these locations, the Institution also has a designated examination centre in Dubai.

During these semesters, in addition to the above mentioned Mid-Semester and Comprehensive examinations, there will also be Quizzes/Assignments conducted online on the Learning Management System (LMS) as per the course plan in which the students need to participate.

In Semester 4 (Final Semester), the student will be doing Dissertation/Project Work as per the Institution’s guidelines.

Eligibility Criteria

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.
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.
Working knowledge of Computing and programming is required.

Fee Structure

The following fees schedule is applicable for candidates seeking new admission during the academic year 2024-2025.

Application Fees (one time) : INR 1,500
Admission Fees (one time) : INR 16,500
Semester Fees (per semester) : INR 71,750

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. 85,000/-. You may choose to make the payment using Netbanking/ Debit Card/ Credit Card through the Online Application Centre.Fee payment by easy-EMIs with 0% interest. Click here to learn more.

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.

For the examination centre at Dubai, in addition to the semester fees, for each semester there will be an examination centre fees of 1000 UAE Dirhams or equivalent per semester out of which 500 UAE Dirhams is to be paid at the time of appearing in Mid-semester examinations at Dubai Centre for that semester and the remaining 500 UAE Dirhams is to be paid at the time of appearing in comprehensive examinations at Dubai centre for that semester.

All the above fees are non-refundable.

Important: For every course in the program institute will recommend textbooks, students would need to procure these textbooks on their own.

How to Apply

Once your login has been created, you can anytime access the Online Application Center using your email id and password. Once you have logged in, you will see a screen showing 4 essential steps to be completed to apply for the programme of your choice.
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 the details and press ‘Submit’ button given at the bottom of the form.
Take the next step by clicking on Step 2 - 'Download Application PDF Copy’. This will download a pdf copy of the application form on your computer.
Now, click on Step 3 - 'Pay Application Fee’ to pay INR 1,500/- using Netbanking/ Debit Card/ Credit Card.
Take a printout of the downloaded Application Form and note down the Application Form Number displayed on the top-right corner of the first page. This Application Form Number should be referred in all future correspondence with BITS Pilani.
In the printout of the downloaded Application Form, you will notice on page no. 3 a section called the Employer Consent Form. Complete the Employer Consent Form. This form needs to be signed and stamped by your organisation’s HR or any other authorised signatory of the company.

Important: In view of work-from-home policies mandated by many organisations, a few candidates may not be able to get the physical forms signed by their HR/ other authorised organisational representative. Such candidates may instead request an email approval to be sent to their official email ID by the HR using the format available through this link.
Role of a Mentor: The basic role of the mentor will be to ensure that the student remains aligned with the academic objectives and the key academic milestones while pursuing the programme. The mentor’s valuable guidance and professional expertise would also be leveraged to maximise work-integrated learning and make the education experience highly relevant for the job role and pursuit of the long-term career goals of the student. Following are the expected responsibilities of the mentor:

1. Periodically monitor student’s study schedules and submission deadlines for the programme.

2. Provide guidance towards integrating learning from the programme with job role/long-term career goals, especially while the student pursues their learning assignments and project work.

3. Monitor the student’s progress throughout the duration of the programme. If required by BITS Pilani, also try to be available to engage with the faculty to collaboratively assess the student’s academic performance and recommend any learning improvement plan.

4. Emphasise the importance of self-study and self-learning throughout the programme to the student.

Qualifications for a Mentor:The mentor chosen should be a senior professional with at least 5 years of relevant work experience, holding a B.E./ B.Tech./ M.Sc./ M.B.A./ M.B.B.S./ First Degree at BITS Pilani or its equivalent. If the mentor has less than 5 years of relevant work experience, then the minimum educational qualification for the mentor should be M.E./ M.Tech./ M.S./ M.Phil./ Higher Degree of BITS Pilani or its equivalent is required.
Further on page no. 5 of the downloaded Application Form, is a Checklist of Enclosures/ Attachments.
Make photocopies of the documents mentioned in this Checklist.
Applicants are required to self-attest all academic mark sheets and certificates.
Finally, click on Step 4 - 'Upload & Submit All Required Documents’. This will allow you to upload one-by-one the printed Application Form, Mentor Consent Form, Employer Consent Form, and all mandatory supporting documents 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.

Note: It is also possible that some candidates may receive a link to take an Online Learning Readiness Evaluation from the Admission Cell, after filling up the Online Application Form. This is a one-hour objective-type exercise which will ascertain minimum mathematical and programming acumen needed to pursue the programme. You will be given typically 48-hours to complete this online evaluation.

A sample model paper will also be provided to help you understand the format of Online Learning Readiness Evaluation. After the Online Learning Readiness Evaluation is completed, the Admission Cell will intimate selected candidates by email within one week.

Batch Profile

FAQs

Contact classes are conducted over a technology enabled platform. These classes can be attended via the internet using a computer from any location. These contact classes offer similar levels of interactivity as regular classrooms at the BITS Pilani campus. These are conducted usually over weekends or after business hours for a total of 7-8 hours per week. If you miss a lecture, you can also access the recorded lecture on the internet.

This programme is designed for working professionals. At the time of submitting the application, candidates must be employed in another organization. Professionals who are owners of a registered business are also eligible to apply. For detailed information, including academic background, work experience, etc. refer to the programme eligibility criteria.

Upon successful completion of the programme, participants will receive a degree certificate from BITS Pilani.

The Degree of Master of Technology in Artificial Intelligence & Machine Learning

Each semester has a Mid-semester Exam and a Comprehensive Exam for each course , which are conducted over weekends. Students will need to appear in-person to take these exams at exams centers in the following locations:
India Centers:

South Zone: Bangalore, Chennai, Hyderabad, Vijayawada, Visakhapatnam, Kochi, Thiruvananthapuram and Coimbatore.

North Zone: Delhi NCR, Jaipur, Chandigadh, Lucknow and Pilani.

West Zone: Mumbai, Pune, Goa, Ahmedabad, Indore and Nagpur.

East Zone: Kolkata, Bhubaneshwar, Guwahati and Jamshedpur.
International Centers: Dubai
In case students are unable to take an exam due to work-related commitments, there is also a provision of appearing for Make-up Exams.

The programme provides a high degree of interactivity between students and the faculty members and programme instructors. Q&A sessions during the contact classes (which you can attend from anywhere over a technology enabled platform) allow participants to pose questions to the faculty members, and seek guidance through voice and chat. Further interaction with faculty members and peers is enabled through the e-learning portal, by using discussion forums and message boards.

The programme features high usage of experiential learn components such as Simulations, Virtual Labs, and Remote Labs, in order to mimic the on-campus experience.

Participants will be given access to portals, that will allow them to access both cloud-based labs, as well as Campus-based physical labs. Using leading industry-recognised Software tools, Programming languages, and Simulation software, participants will be able to perform experiments and run simulations to advance their knowledge

Candidates applying to the programmes must choose a Mentor, who will monitor the academic progress of the candidate, and act as an advisor & coach for successful completion of the programme. Candidates should ideally choose the immediate supervisor or another senior person from the same organisation. In case a suitable mentor is not available in the same organisation, a candidate could approach a senior person in another organisation who has the required qualifications. For detailed information, please refer to the programme brochure.

The programme is designed for working professionals, and participants are not required to travel to a BITS campus. However, certain programme offer Campus Immersion Modules such as workshops or seminars, which are highly recommended but not mandatory.

Yes, UGC has approved the continued offering of M.Tech. Artificial Intelligence and Machine Learning as a part of WILP on the recommendations of Empowered Expert Committee. Click here to learn more.

It is a post-graduate programme that focuses on providing advanced knowledge and skills in the fields of artificial intelligence and machine learning. The programme covers topics such as machine learning, natural language processing, neural networks, computer vision, robotics, deep learning, data analysis and more.

Applicants for the M.Tech. in Artificial Intelligence and Machine Learning program must meet these criteria:

Employed professionals with a B.E. / B.Tech. or equivalent degree, securing at least 60% aggregate marks
Possessing a minimum of one year of relevant work experience post-degree completion, are eligible to apply.
In addition, a working knowledge of computing and programming is required.

(Or)

Employed professionals with an MCA / M.Sc. or equivalent degree, achieving at least 60% aggregate marks,
With mandatory subjects in mathematics or statistics at the university level,
Possessing a minimum of one year of relevant work experience post-degree completion, are also eligible to apply.
In addition, a working knowledge of computing and programming is required.

Graduates in M.Tech. in Artificial Intelligence and Machine Learning programme are currently in high demand due to the increasing adoption of AI and ML technologies across industries, such as IT, Retail, Automotive, Manufacturing, Finance, Healthcare, e-commerce, and Telecommunications. Some of the job roles that graduates can explore include AI engineer, ML engineer, Data scientist, Data analyst, and Research scientist.

Candidates should have a strong foundation in mathematics, statistics, and programming. Additional, skills, such as data analysis, machine learning, natural language processing, computer vision, problem-solving, and critical thinking would be bonus.

The M.Tech. in Artificial Intelligence and Machine Learning programme spans over two years and is divided into four semesters.