Artificial Intelligence (AI)

Data structures, algorithms, software engineering, and programming in contemporary languages like Python are among the fundamental computer science principles that graduates will get a thorough understanding of. Building scalable AI solutions and comprehending system-level ramifications require this basis.

Using supervised, unsupervised, and reinforcement learning approaches, students will acquire practical experience creating machine learning models. Additionally, they will become proficient in deep learning methods including recurrent neural networks (RNNs), convolutional neural networks (CNNs), and other cutting-edge architectures.

Students will get the ability to create intelligent systems that can process and comprehend human language as well as decipher visual information. This includes creating recommendation engines, chatbots, and computer vision-based programs like facial recognition and object identification.

Students will gain proficiency with well-known AI programming tools and frameworks, including Scikit-learn, OpenCV, PyTorch, TensorFlow, and Keras. Additionally, they will learn how to use scalable deployment techniques and containerization to deploy AI apps on cloud platforms such as AWS, Azure, or Google Cloud.