Overview
The Bachelor of Computer Applications (BCA) with a specialization in Artificial Intelligence (AI) and Machine Learning (ML) is a 3 years innovative program designed to equip students with the knowledge and skills necessary to excel in the rapidly evolving field of AI and ML. Through a combination of theoretical insights and hands-on practical experience, students gain a deep understanding of foundational concepts, algorithms, and techniques essential for developing intelligent systems and leveraging data-driven approaches.
What You’ll Learn
This specialized BCA program delves into topics such as machine learning, deep learning, natural language processing, and reinforcement learning, empowering students to tackle real-world challenges in diverse domains such as healthcare, finance, marketing, and robotics.
Practical Skills
With a strong emphasis on project-based learning and industry-relevant course work, graduates of this program emerge as proficient AI and ML practitioners capable of designing innovative solutions, analyzing complex datasets, and driving technological advancements in the digital era.
Career Pathways
- AI Engineer
- Machine Learning Engineer
- Data Scientist
- Natural Language Processing (NLP) Engineer
- Deep Learning Engineer
- Business Intelligence Analyst
- AI Consultant
- Research Analyst
- Software Developer (AI and ML Focus)
Programme Education Objectives
PEO
Programme Educational Objectives
PEO1
Provide a strong foundation in computing on key domains of AI and develop core competencies in designing AI based solutions to real-world problems.
PEO2
Provide opportunities to explore research areas and develop outstanding solutions in various areas of Artificial Intelligence and Machine Learning.
PEO3
Equip students with excellent technical, communication and leadership skills and nurture them to become ethically and socially responsible solution providers with specialization in the field of AI.
PEO4
Provide training in AI project development and research methods which includes analysis, designing algorithms as solutions to solve real-world problems and inculcate ethical and moral values.
PEO5
Encourage students to become entrepreneurs and to practice continuous learning in order to achieve professional and personal excellence.
Programme Outcomes (POs)
On completion of the BCA AI & ML programme, the student will be able to:
PO
Programme Outcomes
PO1
Acquire core competencies in the field of Artificial Intelligence and use data analytics tools to develop solutions for complex decision-making problems.
PO2
Develop strong programming skills and design algorithms that incorporate mathematical and statistical perspectives to build decision-making applications.
PO3
Possess strong technical, communication and leadership skills, collaborate effectively in teams and create innovative AI solutions aligned with legal, moral and ethical principles.
PO4
Explore solutions for complex problems using research methods and design AI solutions that meet specific needs while considering cultural, societal and environmental factors.
PO5
Adapt to technological advancements through life-long learning and become successful professionals or entrepreneurs contributing meaningfully to society.
Programme Structure
Semester I
Semester II
Semester III
Semester IV
Semester V
Semester VI
Language I – Kannada: Saahitya Sangama – I, Hindi: Gadya Sampada, Additional English: Translations selected from South India
Language I – Kannada: Saahitya Sangama – II, Hindi: Gadya Deep, Additional English: Translations selected from East and North East India
Language I – Kannada: Saahitya Sinchana – I, Hindi: Kavya Pankaj, Additional English: Translations selected from Central and West India
Language I – Kannada: Saahitya Sinchana II, Hindi: Khand Kavya Nahush, Additional English: Translations selected from North India
Big Data and NoSQL
Deep Learning
Language II – Generic English: Readings from Literature and Language Skills
Language II – Generic English: Interpretations of Literature and Language Skills
Language II – Generic English: Perceptions of Literature and Language Skills
Language II – Generic English: Insights from Literature and Language Skills
Software Project Management
Natural Language Processing
Discrete Mathematics
Computer Architecture
Operating System and Unix Programming
Design and Analysis of Algorithms
Machine Learning
Deep Learning and Natural Language Processing Lab
Problem Solving Techniques using C
Data Structures
Statistics and Probability
Artificial Intelligence
NoSQL Lab
Data Visualization Lab
Database Management Systems
Object Oriented Programming Using Java
Python Programming
R Programming
Machine Learning Lab
Project Lab
C Programming Lab
Data Structures Lab
Unix Programming Lab
Artificial Intelligence Lab
SEC: Aptitude and Reasoning
SEC: Professional Business Communication
DBMS Lab
Java Lab
Python Programming Lab
R Programming Lab
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Constitution of India
Environmental Studies
Elective I
1.Cloud Computing
2.Computer Animation
3.OOAD Using UML
Elective II
1.Block Chain Technology
2.Internet of Things
3. Cryptography and Network Security
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Constitutional Moral Values
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Semester I
| Course Code | Name of Course | Teaching Hours | Credits |
|---|---|---|---|
| 25SKN 1.1 / 25SHN 1.1 / 25ADE 1.1 | Language I – Kannada: Saahitya Sangama – I, Hindi: Gadya Sampada, Additional English: Translations selected from South India | 60 | 3 |
| 25GEN 1.1 | Language II – Generic English: Readings from Literature and Language Skills | 60 | 3 |
| 25AMLDC 1.1 | Discrete Mathematics | 56 | 4 |
| 25AMLDC 1.2 | Problem Solving Techniques using C | 56 | 4 |
| 25AMLDC 1.3 | Database Management Systems | 56 | 4 |
| 25AMLDC 1.4 | C Programming Lab | 45 | 2 |
| 25AMLDC 1.5 | DBMS Lab | 45 | 2 |
| 24VBC 1.1 | Constitution of India | 30 | 2 |
| Total Credits | 24 |
Semester II
| Course Code | Name of Course | Teaching Hours | Credits |
|---|---|---|---|
| 25SKN 2.1 / 25SHN 2.1 / 25ADE 2.1 | Language I – Kannada: Saahitya Sangama – II, Hindi: Gadya Deep, Additional English: Translations selected from East and North East India | 60 | 3 |
| 25GEN 2.1 | Language II – Generic English: Interpretations of Literature and Language Skills | 60 | 3 |
| 25AMLDC 2.1 | Computer Architecture | 56 | 4 |
| 25AMLDC 2.2 | Data Structures | 56 | 4 |
| 25AMLDC 2.3 | Object Oriented Programming Using Java | 56 | 4 |
| 25AMLDC 2.4 | Data Structures Lab | 45 | 2 |
| 25AMLDC 2.5 | Java Lab | 45 | 2 |
| 24VBC 2.1 | Environmental Studies | 30 | 2 |
| Total Credits | 24 |
Semester III
| Course Code | Name of Course | Teaching Hours | Credits |
|---|---|---|---|
| 24SKN 3.1 / 24SHN 3.1 / 24ADE 3.1 | Language I – Kannada: Saahitya Sinchana – I, Hindi: Kavya Pankaj, Additional English: Translations selected from Central and West India | 60 | 3 |
| 24GEN 3.1 | Language II – Generic English: Perceptions of Literature and Language Skills | 60 | 3 |
| 24AMLDC 3.1 | Operating System and Unix Programming | 56 | 4 |
| 24AMLDC 3.2 | Statistics and Probability | 56 | 4 |
| 24AMLDC 3.3 | Python Programming | 56 | 4 |
| 24AMLDC 3.4 | Unix Lab | 45 | 2 |
| 24AMLDC 3.5 | Python Programming Lab | 45 | 2 |
| 24AMLDC 3.6X | Elective I | 45 | 3 |
| 24VBC4.1 | Constitutional Moral Values | 30 | 2 |
| Total Credits | 27 |
Elective I:
- 24AMLDE 3.6a Cloud Computing
- 24AMLDE 3.6b Computer Animation
- 24AMLDE 3.6c OOAD Using UML
Semester IV
| Course Code | Name of Course | Teaching Hours | Credits |
|---|---|---|---|
| 24SKN 4.1 / 24SHN 4.1 / 24ADE 4.1 | Language I – Kannada: Saahitya Sinchana – II, Hindi: Khand Kavya Nahush, Additional English: Translations selected from North India | 60 | 3 |
| 24GEN 4.1 | Language II – Generic English: Insights from Literature and Language Skills | 60 | 3 |
| 24AMLDC 4.1 | Design and Analysis of Algorithms | 56 | 4 |
| 24AMLDC 4.2 | Artificial Intelligence | 56 | 4 |
| 24AMLDC 4.3 | R Programming | 56 | 4 |
| 24AMLDC 4.4 | Artificial Intelligence Lab | 45 | 2 |
| 24AMLDC 4.5 | R Programming Lab | 45 | 2 |
| 24AMLDE 4.6X | Elective II | 45 | 3 |
| Total Credits | 25 |
Elective II:
- 24AMLDE 4.6a Block Chain Technology
- 24AMLDE 4.6b Internet of Things
- 24AMLDE 4.6c Cryptography and Network Security
Value Added Courses (VACs)
| S.No | Name of the VAC |
|---|---|
| 1 | Mobile Application Development |
| 2 | 2D Animation |
| 3 | Hands on cloud computing on AWS |
| 4 | Cyber Security |
| 5 | Data Analysis using Spreadsheet |
| 6 | Ethical hacking |
| 7 | Web Application development- Front end |
| 8 | Web Application development- Back end |
Eligibility Criteria
Candidates who have completed two-years pre-university programme of Karnataka State or its equivalent of any state or country or a candidate who has passed JODC/three-year diploma in engineering (Government of Karnataka) are eligible for admission into this programme.
- Pass in 10 + 2 are eligible for BCA (AI and ML) admission.