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Master of Computer Applications (MCA) with Specialisations

Artificial Intelligence and Machine Learning


The Applicant should have passed BCA / Bachelor Degree in Computer Science Engineering or equivalent Degree. OR passed B.Sc./ B.Com./ B.A. with Mathematics at l0+2 Level or at Graduation Level (with additional bridge Courses as per the norms of the concerned University). Obtained at least 50 % marks (45 % marks in case of candidates belonging to reserved category) in the qualifying Examination.

In addition to the above, the Applicant must pass both an entrance exam and a personal interview as per the University requirements.


The Artificial Intelligence market size is expected to reach $65.48 billion by 2020. According to the projections made for the year 2030, this value is to reach $1,581.70 Billion, increasing at the rate of 38.0% of CAGR from the year 2021 to 2030. AI has almost become synonymous with the future of technology. With AI outperforming human efforts, organizations are opting for AI more and more to increase efficiency and slash down costs in the long run. AI along with Big Data, ML, and NLP are ranked 2nd amongst the top tech priorities for 2021-2 according to NASSCOM Tech CEO Survey 2022.

Across all industries, there is a growing need for intelligent and accurate decision-making systems. As a result, AI and ML technologies have seen exponential growth, and they are likely to remain relevant for many years to come. Machine Learning is a subset of Artificial Intelligence that aids programs advance their prediction precision by utilizing old databases. Artificial Intelligence has already begun showing its effects in the form of convenience that it has provided humans with. The main focus of AI and ML is to create machines and programs that have problem-solving skills and goals like human beings. The scope of AI and ML lies in the industries of technology, financial services, military, and national security, gaming, agriculture, healthcare, and many more.

Course Highlights
  • Develop programming, analytical and logical thinking abilities. 
  • Develop computational knowledge and project development skills to solve societal problems in AI & ML
  • Develop the ability to qualify for Employment, higher studies, and Research in Artificial Intelligence and Data science with ethical values. 
  • Inculcate the ability to work in a team and act as an individual in a multidisciplinary environment with lifelong learning and social awareness.
  • The ability to apply knowledge of fundamentals, specializations, mathematics, and domain knowledge to problem-solving and creating computing models that represent an abstraction of requirements
  • Problem Analysis: Identify, formulate, design, and solve complex computing problems providing concrete conclusions using fundamental principles of mathematics, computing sciences, and relevant domain disciplines. 
  • Develop solutions to problems in computing by constructing components, implementing processes, and evaluating solutions that meet defined specifications
  • Modern Tool/Techniques usage: Select, adapt, and apply appropriate tools, techniques, resources to various computing activities, with an understanding of their limitations
  • Professional Ethics: Understand and commit to professional ethics and cyber regulations, responsibilities, and norms of professional computing practices
  • Life-long learning: Recognize the need and have the capability to engage in independent learning for continuous professional development. 
  • Communication Efficiency: Communicate effectively about computing activities with the computing community, and with society at large, through the ability to comprehend and write effective reports, design documentation, deliver effective presentations, and give and understand clear instructions.
  • Societal and Environmental Concern: Understand and assess societal, environmental, health, safety, legal, and cultural issues within local and global contexts, and the consequential responsibilities relevant to professional computing practices. 
  • Individual and Teamwork: In a multidisciplinary environment and diverse teams, function as an effective individual, member, or leader.
  • Innovation and Entrepreneurship: Create value and wealth for the individual and society at large by identifying a timely opportunity and using innovation to pursue that opportunity.
  • Conduct Investigations of complex computing problems: Apply research-based knowledge and research methods, including the design of experiments, the analysis and interpretation of data, and the synthesis of the information to provide valid conclusions. 
  • Project management and finance: The ability to understand and apply computing and management principles to one's own work, as a leader or as a member of a team, in order to manage projects in a multidisciplinary environment.
Program code: 045B
Course code : 45B5
Course Commencement : Sep 2024

Study Campus

School of CS and IT
#44/4, District Fund Road
Jayanagar 9th Block
Bangalore - 560069
080 - 46501773

Admissions Office

JAIN Knowledge Campus
# 44/4, District Fund Road
Jayanagar 9th Block Campus
Bangalore - 5600 69
080 - 46501773
+91 7337615222

Course Image
Curriculum Structure

Core Subjects
  • Data Structures
  • Advanced Computer Networks
  • Advanced Operating Systems
  • Mathematical Foundation for Computer Applications
  • Advanced Computer Architecture
  • Open Elective-1
Minor Electives
  • Advanced Software Engineering
  • Fundamentals of Cloud Computing
  • Essentials to Cyber Security
Learning Labs
  • Data Structures Lab
  • Advanced Computer Networks Lab
  • Advanced Operating Systems Lab

Core Subjects
  • Advanced Database Management Systems
  • Object Oriented Programming using JAVA
  • Artificial Intelligence
  • Machine Learning Using Python
  • Business Data Modelling
  • Open Elective-2
Minor Electives
  • Agile Software Development Approaches
  • Ethical Hacking
  • Fundamentals of server Operating system
Learning Labs
  • Advanced Database Management Systems Lab
  • Object Oriented Programming using JAVA Lab
  • Machine Learning Using Python Lab
  • Research Methodology
  • PCL 1 Research and Entrepreneurship Project

Core Subjects
  • Advanced Probability Statistics
  • Deep Learning
  • Predictive Analytics and Data Visualisation
  • Big Data Analytics
  • Natural Language Processing
  • Open Elective-3
Minor Electives
  • Software Quality Assurance and Testing
  • Cloud Web services
  • Cyber Forensics
Learning Labs
  • Deep Learning Lab
  • Predictive Analytics and Data Visualization Lab
Projects / Internship Lab
  • Mini Project Lab
  • Summer Internship

Core Subjects
  • Open Elective-4
Minor Specialisation Course - 4
  • Software Project Management
  • Server Administration
  • Cyber Law
  • Project/Internship
  • PCL-2 Research and Entrepreneurship Project
  • Research Publications
Career Outcomes

The job outlook for AI-ML professionals is extremely promising nowadays, the number of AI start-ups in India has shot up in recent years. It is expected that this number is going to keep rising in the future, which implies an abundance of career opportunities. Searching LinkedIn recently for "artificial intelligence" jobs revealed more than 45,000 results at a range of companies. The students pursuing our Master’s degree in AI and ML will have opportunities to become:

  • AI & ML Engineer/Developer: Responsible for performing statistical analysis, running statistical tests, and implementing statistical designs. Furthermore, they manage ML programs, implement ML algorithms, and develop deep learning systems.
  • AI Analyst/Specialist: The key responsibility is to cater to AI-oriented solutions and schemes to enhance the services delivered by a certain industry using the data analyzing skills to study the trends and patterns of certain datasets.
  • Business Intelligence (BI) Developer: An engineer that’s in charge of developing, deploying, and maintaining BI interfaces. The list includes query tools, dashboards, interactive visualizations, ad hoc reporting, and data modeling tools.

And other exciting roles in the market like Human-centered Machine Learning Designer, Data Architect, Research Scientist, NLP Engineer.

Potential employers/stakeholders identified Data-driven organizations, companies in Artificial Intelligence & Data Science domains focused on sectors like Information technology & Services, Consumer goods, Manufacturing, and various other sectors.