BCA (Artificial Intelligence and Data Science)
Introduction to course
The Bachelor of Computer Applications (BCA) in Artificial Intelligence and Data Science is a cutting-edge program designed to equip students with the knowledge and skills needed to thrive in the rapidly evolving tech landscape. This course combines foundational computer science principles with specialized training in AI and data science, enabling students to develop innovative solutions for complex problems. Through a blend of theoretical coursework, practical projects, and industry internships, students will gain expertise in machine learning, data analytics, and intelligent systems, preparing them for diverse careers in technology, research, and beyond.
Mission
The mission of the BCA (Bachelor of Computer Applications) program specializing in Artificial Intelligence and Data Science is to equip students with a robust foundation in computer science while focusing on cutting-edge technologies like AI and data science. Through a blend of theoretical knowledge and practical skills, the course aims to nurture future-ready professionals capable of innovating and solving complex challenges in AI-driven applications and data-centric environments. The program strives to foster critical thinking, creativity, and ethical responsibility, preparing graduates to thrive in diverse industries where AI and data science are pivotal to shaping the future of technology and society.
Vision
A Bachelor of Computer Applications (BCA) program specializing in Artificial Intelligence and Data Science equips students with a robust foundation in both theoretical concepts and practical skills essential for navigating the digital age. This course integrates core computer science principles with specialized training in machine learning, data analysis, and algorithms, preparing graduates to innovate across industries. Students delve into programming languages like Python and R, explore advanced data manipulation techniques, and learn to leverage AI tools for predictive analytics and automation. The curriculum emphasizes real-world applications, ethical considerations in AI development, and collaborative projects, ensuring graduates are adept problem solvers ready to drive technological advancements and data-driven decisions in diverse organizational settings.
Course objective
- Fundamental Knowledge: Gain a comprehensive understanding of computer science fundamentals, mathematics, and statistics essential for AI and data science applications.
- Programming Skills: Develop proficiency in programming languages such as Python, R, and SQL to manipulate and analyze large datasets.
- Machine Learning Techniques: Learn advanced machine learning algorithms and models for predictive analytics, pattern recognition, and data mining.
- Data Visualization: Acquire skills in data visualization tools like Tableau and matplotlib to effectively communicate insights from complex datasets.
- Big Data Technologies: Explore big data technologies such as Hadoop and Spark for managing and processing massive volumes of structured and unstructured data.
- Ethical Considerations: Understand the ethical implications and legal frameworks surrounding data privacy, security, and responsible AI deployment.
- Project-Based Learning: Apply theoretical knowledge through hands-on projects in areas like natural language processing, image recognition, and predictive modeling.
- Industry Readiness: Prepare for careers in AI and data science through industry-relevant coursework, internships, and guest lectures from professionals in the field.
- Research and Innovation: Encourage research-oriented thinking to explore cutting-edge technologies and contribute to the advancement of AI and data science applications.
- Continuous Learning: Foster a mindset of lifelong learning to adapt to evolving technologies and emerging trends in AI and data science.
These objectives aim to equip students with the skills and knowledge necessary to excel in the rapidly growing fields of Artificial Intelligence and Data Science.
Course outcome
A BCA in Artificial Intelligence and Data Science equips you with a strong foundation in computer science principles, mathematics, and core AI and Data Science concepts. By the time you graduate, you’ll be able to apply critical thinking and problem-solving skills to tackle complex computing challenges using appropriate tools and programming languages. You’ll also gain expertise in areas like data structures, algorithms, database management, and web technologies. Most importantly, you’ll develop the ability to design, implement, and analyze AI and Data Science solutions for real-world problems.
Admission procedure
Check Eligibility (Physics + Maths + Chemistry / Computer)
|
Board |
Category |
Theory Marks |
Theory + Practical Marks |
|---|---|---|---|
|
GSEB |
Open |
135 / 300 |
180 / 400 |
|
GSEB |
Reserve |
120 / 300 |
180 / 400 |
|
Other Boards |
Open |
108 / 240 |
135 / 300 |
|
Other Boards |
Reserve |
96 / 240 |
120 / 300 |
Required Documents
- SSC
- HSC
- GUJCET mark-sheet
- Leaving certificate (applicable for all)
- Income certificate
- Caste certificate, NCL (if applicable)
Curriculum
- Duration: 4 years
- Fees: Rs. 70,000
- Intake: 60
| GTU Code | Subject | Theory(Hrs) | Tutorial(Hrs) | Practical(Hrs) | Credits |
|---|---|---|---|---|---|
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| GTU Code | Subject | Theory(Hrs) | Tutorial(Hrs) | Practical(Hrs) | Credits |
|---|---|---|---|---|---|
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| GTU Code | Subject | Theory(Hrs) | Tutorial(Hrs) | Practical(Hrs) | Credits |
|---|---|---|---|---|---|
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| GTU Code | Subject | Theory(Hrs) | Tutorial(Hrs) | Practical(Hrs) | Credits |
|---|---|---|---|---|---|
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| GTU Code | Subject | Theory(Hrs) | Tutorial(Hrs) | Practical(Hrs) | Credits |
|---|---|---|---|---|---|
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| GTU Code | Subject | Theory(Hrs) | Tutorial(Hrs) | Practical(Hrs) | Credits |
|---|---|---|---|---|---|
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| GTU Code | Subject | Theory(Hrs) | Tutorial(Hrs) | Practical(Hrs) | Credits |
|---|---|---|---|---|---|
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| GTU Code | Subject | Theory(Hrs) | Tutorial(Hrs) | Practical(Hrs) | Credits |
|---|---|---|---|---|---|
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
| 3110000 | Lorem Ipsum | 0 | 0 | 0 | 0 |
Labs and facilities
Photo gallery
