BCA in Artificial Learning & Machine Learning (AL-ML) at Maharishi University of Information Technology - Course, Fees, Admission, Seats, Syllabus

Based on my recent update in April 2023 the specific course curricula can vary between institutions and may change over time. However if you're pursuing a Bachelor of Computer Applications (BCA) degree with a focus on Artificial Learning (AL) and Machine Learning (ML) at a university like Maharishi University of Information Technology there are some topics that are likely to be emphasized. Here's a list of subjects that students in this program might expect to study; 1. **Introduction to Programming**; This course would cover the fundamentals of programming languages like Python, which is widely used in AI and ML projects. 2. **Mathematics for Machine Learning**; This subject would delve into mathematical concepts such as linear algebra, calculus and statistics. These foundations are crucial for understanding and developing ML algorithms. 3. **Data Structures and Algorithms**; In this course students would learn about data structures and algorithms that play a vital role in efficiently solving computer science problems. They'll also explore how these concepts apply to AI and ML. 4. **Database Management Systems**; This subject focuses on understanding the principles behind database management systems, including SQL. Proficiency in SQL is important, for handling datasets commonly used in ML projects. 5. **Introduction to Artificial Intelligence**; This course provides an overview of AI covering topics such as search algorithms, knowledge representation, reasoning and the fundamental principles of machine learning. 6. **Machine Learning**; This module delves into the study of ML algorithms, including learning (such as linear regression, decision trees, support vector machines) unsupervised learning (such as clustering and dimensionality reduction) and deep neural networks. 7. **Exploring Deep Learning**; In this section we focus on advanced ML models like Convolutional Neural Networks (CNNs) Recurrent Neural Networks (RNNs) and techniques like transfer learning. 8. **The Power of Natural Language Processing (NLP)**; Gain insights into the techniques used to enable computers to understand and interpret languages naturally. This knowledge is crucial for applications like chatbots and sentiment analysis. 9. **Unveiling Computer Vision**; Discover how computers can gain high level understanding from images or videos. This module covers topics such as recognition, object detection and more. 10. **Mastering Reinforcement Learning**; Dive into the realm of ML that deals with how software agents make optimal actions, within an environment to maximize rewards. 11. **. The Social Impact of AI**; Exploring the ethical implications and societal consequences associated with the implementation of AI and ML technologies, including concerns, about privacy, bias and potential job displacement. 12. **Final Project**; Usually these programs include a culminating project where students can showcase their skills and knowledge.