🤖 B.Tech in Artificial Intelligence & Machine Learning

The AI & ML branch focuses on building intelligent systems capable of learning, reasoning, and decision-making. Students gain expertise in designing algorithms, training models, and deploying AI solutions across industries.

The curriculum covers machine learning algorithms, deep learning, computer vision, natural language processing, reinforcement learning, big data analytics, cloud-based AI deployment, and ethical AI practices.

• Supervised, unsupervised, and reinforcement learning
• Deep neural networks and convolutional networks
• Natural language processing and speech recognition
• Computer vision and image processing
• Big data analytics and AI model deployment
• Cloud AI services (AWS, Azure, Google AI)
• Ethical AI and bias mitigation

• Hands-on coding of ML and AI models using Python, TensorFlow, and PyTorch
• Industry-oriented projects with real datasets
• AI hackathons and Kaggle competitions
• Workshops on generative AI and autonomous systems
• Internships with AI startups and research labs
• Case studies on AI in healthcare, finance, and robotics

• AI model design and deployment projects
• Performance evaluation using accuracy, precision, and recall
• Technical papers and research presentations
• Practical coding assessments
• Viva on AI architecture and algorithms

AI & ML engineers work in autonomous vehicles, recommendation systems, fraud detection, medical diagnostics, predictive analytics, robotics, and conversational AI systems globally.

AI & ML integrates with robotics, data science, IoT, cybersecurity, and even biomedical engineering for smart, data-driven solutions.

By the end of the course, students will be able to:

• Design and implement AI-driven solutions for real-world problems
• Train and optimize ML and deep learning models
• Leverage cloud platforms for scalable AI deployment
• Apply ethical guidelines in AI development
• Innovate in autonomous and intelligent systems