The B.Tech in Computer Science Engineering (AI & ML) is a comprehensive 4-year program designed to equip students with a robust understanding of computer science principles and artificial intelligence techniques. It consists of 8 semesters, blending theoretical coursework with practical training in areas such as machine learning, data analysis, and software development. The curriculum emphasizes hands-on experience through projects, internships, and laboratory work, preparing graduates to address complex challenges in the tech industry, innovate in AI applications, and apply computer science concepts to real-world problems.
Programming Fundamentals: Introduction to programming languages, algorithms, and data structures.
Artificial Intelligence: Understanding the principles of AI, including machine learning, neural networks, and natural language processing.
Machine Learning: Exploration of algorithms and techniques for building predictive models and data-driven solutions.
Data Science: Study of data analysis, data visualization, and statistical methods to extract insights from data.
Software Engineering: Principles of software development, project management, and software lifecycle methodologies.
Cloud Computing: Understanding cloud architecture, services, and deployment models for scalable applications.
Big Data Technologies: Exploration of big data tools and frameworks for processing and analyzing large datasets.
Cybersecurity: Study of security protocols, ethical hacking, and measures to protect systems and data.
Web Development: Design and development of dynamic web applications using front-end and back-end technologies.
Mobile Application Development: Principles and practices of creating applications for mobile platforms.
Artificial Intelligence: Focus on developing intelligent systems and applications using machine learning, natural language processing, and computer vision.
Machine Learning: Specialize in algorithms and techniques for building predictive models and automating data analysis processes.
Data Science: Study the collection, analysis, and visualization of data to extract meaningful insights and support decision-making.
Cybersecurity: Focus on protecting computer systems and networks from cyber threats, including ethical hacking and data encryption techniques.
Cloud Computing: Specialize in cloud architecture, services, and deployment strategies for scalable applications and data storage solutions.
Web Development: Study the design and development of interactive and dynamic web applications using modern front-end and back-end technologies.
Mobile Application Development: Focus on creating applications for mobile platforms, including Android and iOS, using various development frameworks.
The B Tech in CSE (AI & ML) curriculum is designed to integrate theoretical knowledge with practical application, ensuring students are well-prepared for the tech industry. It includes:
Core Subjects: Courses cover programming languages, algorithms, data structures, machine learning, artificial intelligence, and database management systems.
Laboratory Work: Hands-on labs enable students to experiment with coding, software development, and data analysis, reinforcing theoretical concepts.
Project Work: Students undertake design and implementation projects, applying AI and ML techniques to solve real-world problems, fostering innovation and critical thinking.
Internships: Opportunities for industry experience provide exposure to AI applications in various sectors, allowing students to gain practical insights and network with professionals.
Workshops and Seminars: Sessions conducted by industry experts cover the latest trends, tools, and techniques in AI, machine learning, and related fields, enhancing students' knowledge and skills.
Graduates with a degree in Computer Science Engineering specializing in Artificial Intelligence and Machine Learning have numerous career paths, including:
Machine Learning Engineer: Design and implement machine learning models and algorithms to solve complex problems in various industries.
Data Scientist: Analyze and interpret complex data to drive business decisions and develop predictive models using AI techniques.
AI Research Scientist: Conduct research to advance the field of artificial intelligence, focusing on developing new algorithms and technologies.
Software Developer: Create software applications and solutions that leverage AI and ML technologies for improved functionality and performance.
Robotics Engineer: Work on the design and development of intelligent robotic systems that can perform tasks autonomously.
AI Product Manager: Oversee the development of AI-driven products, ensuring they meet market needs and align with business strategies.
Business Intelligence Analyst: Utilize AI tools to analyze data trends and provide insights to enhance decision-making processes in organizations.
Cloud Solutions Architect: Design cloud-based solutions that incorporate AI and ML capabilities for scalability and performance optimization.