Admission Enquiry
HELPLINE:
+91 99164 93679
Programmes
Bachelor of Computer Applications (Honours) - Artificial Intelligence and Machine Learning
Overview
The AI/ML (Artificial Intelligence / Machine Learning) Honors program is an undergraduate degree program that focuses on computer applications and advanced techniques in artificial intelligence and machine learning. This specialized program is designed to provide students with a deep understanding of AI/ML concepts, algorithms, and applications, preparing them for careers in cutting-edge fields such as data science, artificial intelligence, and robotics.
This program equips students with the theoretical knowledge, practical skills, and hands-on experience needed to excel in the rapidly growing field of artificial intelligence and machine learning. Graduates are prepared to pursue careers as AI/ML engineers, data scientists, research scientists, and AI consultants in a wide range of industries.
Duration
Four Years / Eight Semesters
Commence of the course
Course Duration
Four Years
Mode of Study
Eligibility
10+2 from recognized Board / Council with minimum 50% marks.
A relaxation of 5% marks or its equivalent grade may be allowed for those belonging to SC / ST.
Key Areas
Core Computer Science Knowledge:
Develop a strong understanding of fundamental computer science concepts, algorithms, and data structures.
Programming Proficiency:
Acquire proficiency in programming languages commonly used in Artificial Intelligence and Machine Learning. Develop the ability to design, implement, and debug software solutions for Real time-related challenges.
AI & ML Fundamentals:
Gain a comprehensive understanding of key AI & ML concepts, including data preprocessing, supervised and unsupervised algorithms, exploratory data analysis, and statistical modeling.
Mathematical Foundation:
Build a solid foundation in mathematical concepts essential for classification, regression, and clustering such as linear algebra, calculus, statistics, and probability.
Database Management:
Learn to design, implement, and manage databases for efficient data storage and retrieval.
Machine Learning and Predictive Modeling:
Explore machine learning algorithms and techniques for predictive modeling, classification, and clustering.
Data Visualization:
Develop skills in data visualization to effectively communicate insights and findings from data analysis.
Big Data Technologies:
Understand and work with big data technologies and frameworks such as Hadoop and Spark for processing and analyzing large datasets.
Business Intelligence:
Learn how to extract actionable insights from data to support decision-making in a business context.
Ethical and Legal Considerations:
Understand the ethical and legal implications of working with data, including issues related to privacy and data security.
Project Management and Collaboration:
Develop project management skills to plan, execute, and deliver data science projects on time and within scope. Foster collaboration and effective communication within interdisciplinary teams.
Internship and Practical Experience:
Provide opportunities for internships or real-world projects to allow students to apply their knowledge and skills in practical settings.
Project Work:
A capstone project where students apply their skills to solve real-world problems or a significant internship experience.
Programme Objectives
- To equip students with a well-rounded skill set, preparing them for a successful career in Artificial Intelligence/Machine Learning fields.
- To provide students with a comprehensive understanding of the theoretical foundations, practical applications, and ethical considerations of AI and ML technologies.
Programme Outcomes
Demonstrate a comprehensive understanding of the theoretical principles, algorithms, and methodologies underlying artificial intelligence and machine learning.
Exhibit proficiency in programming languages commonly used in AI and ML development, such as Python, R, and associated libraries and frameworks.
Analyze complex problems, identify suitable AI/ML techniques, and develop innovative solutions to address real-world challenges across various domains.
Possess the skills to collect, clean, preprocess, and transform data, preparing it for use in machine learning models effectively.
Designing, implementing, and optimizing machine learning models for tasks such as classification, regression, clustering, and reinforcement learning, and evaluating model performance using appropriate metrics.
Develop AI-powered applications and systems, integrating machine learning algorithms into software solutions to automate tasks, enhance decision-making, or provide intelligent functionalities.
Understand the ethical considerations and societal impacts associated with AI and ML technologies and apply ethical principles in the design and deployment of AI systems.
Communicate complex AI/ML concepts and findings effectively to both technical and non-technical audiences, through written reports, oral presentations, and visualizations.
Possess strong teamwork and collaboration skills, capable of working effectively in interdisciplinary teams to tackle multidisciplinary projects or research initiatives.
Programme Structure
Curriculum Delivery
Interactive Lectures:
- Conduct engaging and interactive lectures to introduce theoretical concepts related to computer science, programming languages, and game development.
- Use multimedia, presentations, and real-world examples to make the content more accessible and interesting.
Hands-On Coding Sessions:
- Conduct practical coding sessions to reinforce programming skills using languages like Python or R. Hands-on experience is crucial for AI&ML students.
Case Studies and Real-World Projects:
- Engage students with real-world case studies and projects that simulate actual data science challenges. This helps bridge the gap between theory and application.
Interactive Discussions:
- Facilitate discussions on current trends, challenges, and ethical considerations in data science. Encourage students to express their opinions and perspectives.
Workshops and Tutorials:
- Organize workshops and tutorials to provide in-depth guidance on specific tools, frameworks, or methodologies commonly used in AI&ML, such as TensorFlow or sci-kit-learn.
Collaborative Learning:
- Foster a collaborative learning environment where students work together on group projects, share knowledge, and solve problems collectively.
Online Learning Platforms:
- Integrate online learning platforms and resources to provide supplementary materials, quizzes, and interactive exercises. Platforms like Jupiter Notebooks can be particularly useful for AI&ML courses.
Field Visits and Internships:
- Arrange field visits to companies or organizations involved in AI&ML, and encourage students to undertake internships to gain practical experience.
Assessment through Projects and Portfolios:
- Evaluate students based on their performance in hands-on projects, portfolios, and presentations. This allows them to showcase their practical skills.
Research Assignments:
- Assign research projects to encourage students to explore advanced topics in AI&ML, fostering a deeper understanding of emerging trends and technologies.
Career Counseling:
- Provide career counseling sessions to guide students in choosing career paths within the AI & ML industry.
- Assist with resume building, portfolio development, and interview preparation.
By incorporating these methodologies, we can create a dynamic and engaging learning environment for BCA (Hons.) students, preparing them for success in the rapidly evolving field of AI&ML.
Career Opportunities
- Artificial Intelligence / Machine Learning Developer
- Lead Artificial Intelligence / Machine Learning Engineer
- Artificial Intelligence / Machine Learning Architect
- Data Scientist
- Research scientist
- Data Analyst / Scientist
- Business Analyst
- NLP Engineer
- Business Intelligence Developer
- Big Data Engineer
- Big Data Architect
- Quantitative Analyst
- AI (Artificial Intelligence) Engineer
- IoT (Internet of Things) Analyst
- Computer Vision Engineer
FAQ's
The BCA (Honours) in Artificial Intelligence and Machine Learning at Alliance University is taught by highly qualified faculty members with strong academic and research backgrounds. Many of them specialise in areas such as machine learning, edge computing, data analytics, and software engineering, while also contributing to ongoing research and publications. Their blend of academic expertise and industry exposure ensures that students receive a balance of theoretical foundations and practical insights.
Yes. Alliance University has established academic partnerships with reputed universities in the United States, Russia, France, Europe, and Asia, which facilitate student exchange and study abroad opportunities. These initiatives are designed to provide global exposure, broaden perspectives on technology and innovation, and enhance the overall learning experience for BCA (Honours) students.
Students enrolled in the BCA (Honours) in AI and ML programme are encouraged to apply their knowledge through hands-on projects, hackathons, and collaborations with industry partners. These experiential learning opportunities help them design intelligent systems, work with real-world datasets, and develop solutions to contemporary technological challenges. Such exposure ensures graduates are well prepared for careers in data-driven industries.
Applicants must have successfully completed 10+2 or an equivalent examination from a recognised Board with the minimum aggregate marks as specified in the admissions policy of Alliance University. The programme welcomes students with an interest in computing, logical reasoning, and emerging technologies, and admissions are based on a holistic evaluation process.
The BCA (Honours) in AI and ML is complemented by industry-recognised certifications, specialised workshops, and career development initiatives. Students are trained in emerging tools and frameworks through skill-based workshops, while the University’s Career Advancement and Networking (CAN) cell facilitates sessions on employability skills, professional development, and industry readiness.
Yes. The programme includes strong support for internships and placements through Alliance University’s Career Advancement and Networking (CAN) cell. Students benefit from the University’s collaborations with leading technology companies, consulting firms, and start-ups, which provide internship opportunities and full-time placements in roles such as AI Engineer, Data Scientist, and Machine Learning Specialist.
Yes. The curriculum of the BCA (Honours) in AI and ML provides comprehensive training in both Machine Learning techniques and Big Data technologies. Students explore algorithms, predictive modelling, and neural networks while also working with tools that allow them to process and analyse large-scale data effectively.
Graduates of the BCA (Honours) in AI and ML programme are equipped with cutting-edge skills in data science, artificial intelligence, and analytics. This prepares them for a wide range of career opportunities in technology-driven industries, including roles in AI system design, predictive analytics, automation, and software development. The programme also provides a strong foundation for higher studies and specialised research.
The specialisation covers core subjects in computer science, programming, machine learning, and artificial intelligence, supported by practical labs and project-based learning. Students are introduced to industry-standard tools and frameworks to ensure they are workplace-ready upon graduation.
Yes. The curriculum provides extensive training in programming languages widely used in data science and artificial intelligence. Students gain proficiency in Python, R, SQL, and related technologies, which are applied to real-world datasets and AI/ML problem-solving.
The BCA (Honours) in AI and ML is a four-year undergraduate programme structured across eight semesters. The structure balances foundational courses, advanced electives, laboratory sessions, certifications, and industry internships, culminating in a comprehensive capstone project.
Yes. Alliance University offers a range of merit-based scholarships and financial aid opportunities for deserving candidates. The scholarships are awarded based on academic performance, entrance examination scores, and other criteria outlined by the University.
Students of the BCA (Honours) in AI and ML programme have access to advanced computing laboratories, specialised AI and data science labs, cloud computing hubs, and collaborative learning spaces. The University also provides a well-resourced central library, digital databases, and high-speed connectivity to ensure a seamless academic and research experience.
Alliance University’s Career Advancement and Networking (CAN) cell plays a vital role in student career development. Through skill-building workshops, mentorship programmes, industry tie-ups, and dedicated placement support, it ensures that graduates are prepared to secure positions in leading firms such as Deloitte, IBM, Infosys, and other reputed organisations.
Students can connect with alumni through the Alliance Alumni Association portal, professional networking platforms such as LinkedIn, and events facilitated by the Career Advancement and Networking (CAN) cell. These avenues allow current students to seek mentorship, gain industry insights, and build professional connections with graduates who are pursuing diverse career paths.
Contact for Admissions
-
Call Us+91 99164 93679, 080 4619 9045
-
Email Usbca@alliance.edu.in
schools
schools
PROGRAMMES
Important Links
Important Links
Helpline
follow us