B.Voc. in Machine Learning & AI Skills

Machine Learning skills are in great demand in the industry to glean hidden insights from huge volumes of data to work more efficiently and also gain a competitive edge. These skills include data analytics, deep learning, statistical analysis, etc. With the B.VoC program in Machine Learning & AI Skills, in the School of Computing Skills, we will prepare students to be industry-ready in these much sought-after skills. The B.Voc program is modular in nature with multiple exit points at Certificate, Diploma, Advanced Diploma and B.Voc. Each of the six semesters carries 30 credits, resulting in a total of 180 credits for B.Voc.


  • Train to NSQF level 7 in the job role of Data Scientest
  • Train for multiple skill sets in IT, like Deep Learning, Data Analytics,AI,etc
  • Be able to design and implement data-driven products in any company
  • Be eligible to appear in all competitive exams in any goverment sector like UPSC, Defence, Railways and other PSUs
  • Train & equip with knowledge and understanding to become an Entrepreneur
  • Also achieve certification, Diploma and advanced diploma on the way to B.Voc


3 Years

Eligibility Criteria

10+2 PCM or ITI after 10th or Polytechnic Diploma will be considered as equivalent to 10+2

Selection Procedure

Admission will be through an Entrance Exam or based on the merit of the qualifying examination.


B.Voc. (Machine Learning & AI Skills)
Program Structure
Year FIRST SEMESTER   SECOND SEMESTER (Industrial Internship)
  Course Credits Course Credits
I Introduction to computers 4 Industrial Training 15
Understanding Databases 4
Computer Assembling & Peripheral Installation 5
Python Programming 3
Web Development 4 Presentation 3
Open Elective 3 Report 3
Office Software Tools 2 Value Education# 3
English Language & Comprehension 3 Industrial Labour & General Laws# 3
Applied Mathematics 2 Environmental Studies# 3
 Total 30 Total 30
  Cumulative Credits = 30 (Certificate) Cumulative Credits = 60 (Diploma)
Year THIRD SEMESTER   FOURTH SEMESTER (Industrial Internship)
  Course Credits Course Credits
II Artificial Intelligence with Python 4 Industrial Training 15
Machine Learning with Python 3
Statistics with R 3
Data Handling 4
Cloud Computing 3
Open Elective – II 3 Project Report 3
Computer Aided Drawing 3 Presentation 3
Spoken English 3 Organizational Behaviour# 3
Personality Development 2 Business Communication# 3
Entrepreneurship Basics 2 Current Affairs# 3
Total 30 Total 30
Cumulative Credits = 120 (Advanced Diploma)
Year FIFTH SEMESTER   SIXTH SEMESTER (Industrial Internship)
  Course Credits Course Credits
III Deep Learning and Neural Networks 3 Industrial Training 15
Reinforcement Learning 3
Computer Vision and Speech Recognition 4
Natural Language Processing 4
Open Elective – III 3
Digital Marketing 3 Project Report 3
Advanced Communication Skills 3 Presentation 3
Quantitative Aptitude 2 Behavioural Skills# 3
Financial Accounting 2 Indian Constitution# 3
Entrepreneurship Development (Advanced) 3 Technical Writing# 3
Total 30 Total 30
  Cumulative Credits = 180 (B. Voc.)


Career Prospects

It has been predicted that the annual worldwide Al revenue will grow from US$643.7 million in 2016 to US$38.8 billion by 2025. The revenue for enterprise Al applications will increase from US$358 million in 2016 to US$31.2 billion by 2025, representing a compound annual growth rate (CAGR) of 64.3%. Thus Al and Machine learning are exploding, with smart algorithms being used everywhere from email to smartphone apps to marketing campaigns. So if one is looking for an in-demand career, the skills to work with smart machines/artificial intelligence are a great advantage.The student is able to articulate a business problem into a mathematical machine learning problem, and bring value at the end.
Some of the career opportunities in Machine Learning skill are as follows:

  • Fresh graduates or those with only one year’s experience can become Data Science interns in ML techniques like NLP or Python programming
  • Skills in ML can also lead to fresh graduates becoming junior data scientists
  • Graduates with about 3-8 years’ experience, can take up the role of a Data Scientist in Deep Learning
  • Those interested in end-point security can have a career in Automation with ML, for example to recognize file malware threats and deal with them effectively
  • Many jobs are available as Scientist in Analytics and Machine Intelligence