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Course Details
M.Tech Artificial Intelligence and Machine Learning at BITS Pilani is a Work Integrated Learning Program (WLPA) spread over the span of two years and comprises four semesters. The online M.Tech Artificial Intelligence and Machine Learning programme by BITS Pilani equips students with the knowledge and skills required to build careers as Machine Learning Engineers, Artificial Intelligence Engineers, Artificial Intelligence Scientists, and the like. The classes for BITS Pilani Online M.Tech Artificial Intelligence and Machine Learning are conducted online and over the weekends, making the programme suitable for working professionals.
Programme Offerings
- UGC approved online degree
- digital learning
- Continuous Assessment
- Weekend classes
- assignments
- project work
- Supplementary online sessions
- Doubt Clearing Sessions
Eligibility Criteria
Applicants aspiring to enrol in the online M.Tech Artificial Intelligence and Machine Learning programme at BITS Pilani are required to satisfy the eligibility requirements set by the institution. The eligibility criteria for online M.Tech Artificial Intelligence and Machine Learning are as follows:
Applicants must possess a B.E. or B.Tech. degree with a minimum aggregate score of 60% and should have at least one year of work experience following the completion of their degree.
OR
Applicants are required to possess an MCA or M.Sc. degree or its equivalent, with mandatory inclusion of university-level mathematics or statistics and a minimum aggregate score of 60%, along with a minimum of one year of relevant work experience after graduation.
Admission Details
Candidates who meet the eligibility criteria for the BITS Pilani M.Tech Artificial Intelligence and Machine Learning online course can apply for the programme. To initiate the application process, the candidate needs to apply to the programme, provide the required documents, and pay the application fee. Shortlisted candidates would be required to pay the course fee through their preferred mode of payment, such as Netbanking/Debit Card/Credit Card, and the like.
Application Details
In order to fill out the BITS Pilani Online M.Tech Artificial Intelligence and Machine Learning application form, participants must follow these steps:
Visit the official website of BITS Pilani - bits-pilani-wilp.ac.in
Choose online M.Tech Artificial Intelligence and Machine Learning from the list of BITS Pilani courses.
Check that you meet the eligibility criteria.
Click on ‘Apply Now’. You will be led to a registration page.
Register to the BITS Pilani website using your email address.
After registration, login to your account by entering your registered email address and password.
Complete the application process.
Pay the application fee and upload the required documents.
After filling out the application form, candidates may receive an Online Learning Readiness Evaluation authorised by the Admission Cell. This evaluation is an hour-long objective-type assessment that tests the candidate’s skills in mathematics and programming. Candidates will have 48 hours to complete this evaluation. A sample test will be provided to help the candidate understand the format of this evaluation.
Once the evaluation is completed, the Admission Cell will get in touch with shortlisted candidates by email within a week.
The Syllabus
The curriculum of the online M.Tech Artificial Intelligence and Machine Learning at BITS Pilani has been structured over four semesters. The syllabus is divided into mandatory core coursework and elective coursework, of which participants are required to take at least 12 courses. Additionally, they need to complete one project work or dissertation. The detailed BITS Pilani Online M.Tech Artificial Intelligence and Machine Learning syllabus is as follows.
Mathematical Foundations for Machine Learning
Introduction to Statistical Methods
Artificial and Computational Intelligence
Deep Neural Networks
Elective 1
Elective 2
Elective 3
Elective 4
Elective 5
Elective 6
Dissertation
Electives
Pool of Electives for : Deep Learning Specialization
Advanced Deep learning #
Graph Neural Networks
Distributed Machine Learning
ML System Optimization
Fair, Accountable, Transparent Machine Learning
Computational Learning Theory
Note: Three courses are mandatory, including the course marked in #
Pool of Electives for : NLP Specialization
NLP Applications
Speech Processing
Conversational AIx
Social Media Analytics
Information Retrieval
Note: Three courses are mandatory, including the course marked as #
General Pool of Electives
MLOps
Design of Algorithms
Computer Vision
Probabilistic Graphical Models
Audio Analytics
AI and ML for Robotics
Data Management for Machine Learning
Video Analytics
Automated Reasoning
Advanced Data Mining
AI and ML techniques for Cyber Security
Metaheuristics for Optimization
Evaluation Process
Individuals who have enrolled in the M.Tech Artificial Intelligence and Machine Learning programme are required to appear for the online examination. They must have a stable internet connection and a working laptop or personal computer. They can also appear for the examination at the designated examination centres of BITS Pilani, which are located in Bangalore, Chennai, Delhi NCR, Hyderabad, Pune, Mumbai, Kolkata, Goa, and Pilani. A designated examination centre of BITS Pilani is also located in Dubai.
BITS Pilani Frequently Asked Questions (FAQ's)
The programme is specifically designed for working professionals. Candidates applying to the programme must be employed at the time of application.
After completion of the course, BITS Pilani will provide the students with a degree certificate.
The duration of the course is two years, consisting of four semesters.
After graduating from the programme, candidates can pursue careers in a number of fields that require AI and ML to operate, such as IT, finance, e-commerce, healthcare, and others. They can pursue careers as Machine learning engineers, data scientists, AI engineers, Research scientists, and the like.
The classes are conducted over the Internet through live online sessions. Participants need to dedicate 7-8 hours a week to the programme. Also, recorded lectures are available in case students miss any lecture.