BCA in Artificial Learning & Machine Learning (AL-ML) at Bangalore City University - Course, Fees, Admission, Seats, Syllabus

For a Bachelor of Computer Applications (BCA) program that focuses on Artificial Learning and Machine Learning (AL ML) at Bengaluru City University or a similar institution the curriculum is designed to provide a grounding in computer science, mathematics and statistics. It also offers knowledge in the field of artificial intelligence and machine learning. Here are some important subjects typically covered in this program; 1. Foundations of Computer Science; Introduction to Programming; Covers the basics of programming languages like Python, which is widely used in AI and ML. Data Structures and Algorithms; Focuses on organizing and efficiently manipulating data. Computer Architecture and Organization; Provides an understanding of how computersre designed and how they function. 2. Mathematics for AI and ML; Linear Algebra; Covers vectors, matrices and operations essential for comprehending machine learning algorithms. Calculus; Includes integral calculus for understanding optimization problems in ML. Probability and Statistics; Introduces the fundamentals of probability theory and statistics for grasping concepts such as data distributions, sampling and inference that are vital, for ML models. 3. Core Concepts of AI and ML; This section delves into concepts related to artificial intelligence (AI)and machine learning (ML).**Introduction to Artificial Intelligence;** This section provides an overview of AI covering its history, various applications and ethical considerations. **Machine Learning Fundamentals;** The fundamentals of machine learning are discussed here including learning, unsupervised learning and reinforcement learning. **Deep Learning;** This part delves into networks explaining concepts like backpropagation as well as specific types such, as convolutional neural networks (CNNs) and recurrent neural networks (RNNs). A recommended approach, for handling AI/ML projects involves implementing version control using Git and utilizing containers.

Topic	Description
Introduction to AI and ML	Overview of artificial intelligence, machine learning, and their applications.
Python Programming	Basics of Python programming essential for AI and ML.
Data Structures and Algorithms	Understanding of data structures and algorithms for efficient problem-solving in AI/ML.
Mathematics for AI/ML	Linear algebra, calculus, statistics, and probability theory relevant to AI and ML.
Machine Learning Algorithms	Supervised, unsupervised, and reinforcement learning algorithms.
Deep Learning	Neural networks, convolutional neural networks, and recurrent neural networks.
Natural Language Processing	Techniques for processing and analyzing human language.
Computer Vision	Methods for acquiring, processing, analyzing, and understanding digital images.
AI Ethics and Society	Discussion on the ethical implications and societal impacts of AI and ML.
Capstone Project	Practical project to apply AI and ML concepts to solve real-world problems.

This table provides a generic overview of topics that might be covered in a BCA program focusing on Artificial Intelligence and Machine Learning. For the most accurate and specific information, please refer to the official curriculum provided by Bengaluru City University.