BCA in Artificial Learning & Machine Learning (AL-ML) at NSHM Kolkata - Course, Fees, Admission, Seats, Syllabus

As of my last update in April 2023, I don't have access to real-time databases or the specific curriculum details for courses at NSHM Knowledge Campus - Kolkata or any other institutions. However, I can provide you with a generic template for how a BCA in Artificial Learning & Machine Learning (AL-ML) syllabus might be structured across semesters. Please note, for the actual syllabus, you should consult the official NSHM Knowledge Campus - Kolkata website or contact the institution directly.

Semester	Subjects
Semester 1	Introduction to Programming, Mathematics for Computer Science, Introduction to Artificial Intelligence, English Communication, Environmental Studies
Semester 2	Data Structures, Discrete Mathematics, Principles of Machine Learning, Digital Electronics, Psychology
Semester 3	Algorithms, Database Management Systems, Statistics for Machine Learning, Operating Systems, Soft Skills
Semester 4	Object-Oriented Programming, Computer Networks, Deep Learning Fundamentals, Web Technologies, Entrepreneurship Development
Semester 5	Advanced Machine Learning, Natural Language Processing, Big Data Analytics, Elective 1, Project Work 1
Semester 6	Reinforcement Learning, Computer Vision, Elective 2, Project Work 2, Industrial Training

This table is a simplified and generic representation. The actual syllabus might include more specific subjects, practical labs, workshops, and electives tailored to the evolving field of Artificial Learning and Machine Learning. Always refer to the official NSHM Knowledge Campus - Kolkata resources for the most accurate and current information.

Based on my update in April 2023 it may not be possible to directly access specific course details for the BCA program in Artificial Learning & Machine Learning (AL ML) at NSHM Knowledge Campus, Kolkata without referring to the official resources of the institution or contacting them directly. However I can provide you with an overview of the important subjects typically covered in a BCA program that focuses on Artificial Intelligence (AI) and Machine Learning (ML). These subjects serve as a foundation and play a role in comprehending and working within the domains of AI and ML; **Introduction to Programming**; This section covers both basic and advanced programming concepts often starting with languages like Python, which is widely used in AI and ML. **Mathematics for AI and ML**; Here fundamental mathematical concepts such as linear algebra, calculus, statistics and probability are taught. These concepts form the building blocks for understanding and developing AI and ML algorithms. **Data Structures and Algorithms**; Students learn about data structures like arrays, lists, trees and graphs along with algorithms that are essential for solving problems efficiently in AI and ML. **Fundamentals of Artificial Intelligence**; This segment provides an overview of AI including its history, applications across fields as well, as ethical considerations. This may also encompass the field of symbolic AI search algorithms and knowledge representation. **Principles of Machine Learning**; Encompassing the concepts of ML including supervised, unsupervised and reinforcement learning. It also includes known algorithms like linear regression, decision trees and neural networks. **Deep Learning**; Focusing on intricate neural networks such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) which are utilized for tasks like recognizing images and speech. **Natural Language Processing (NLP)**; Concentrating on the processing of language, in a natural manner.I'm interested in exploring techniques that enable computers to comprehend interpret and generate human language. Some of these techniques include computer vision, which focuses on teaching computers how to gain an understanding from digital images or videos such as image recognition and object detection. Additionally I'm intrigued by data analytics and visualization methods that allow us to analyze datasets and extract meaningful insights while visually representing our findings. Another important aspect is considering the implications and legal considerations of deploying AI technologies, including privacy concerns, bias mitigation and accountability. Lastly I find experiences like capstone projects or real world problem solving using AI and ML techniques to be invaluable for applying our knowledge in a tangible way. If you want the accurate and up to date information on the BCA, in Artificial Learning &...