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

As of my update in April 2023 different educational institutions may have varying course curricula. However if you were to pursue a Bachelor of Computer Applications (BCA) program with a specialization in Artificial Intelligence (AI) and Machine Learning (ML) you can expect to cover a range of foundational and advanced topics, in these fields. Here is a general overview of the subjects that such a program might include; **An Overview of Artificial Intelligence**; This section provides an introduction to the history, applications and ethical aspects of AI. **Foundations of Machine Learning**; Here we will explore the basics of machine learning including supervised and unsupervised learning techniques. We'll also cover regression, classification, clustering and dimensionality reduction methods. **Understanding Deep Learning**; In this part we'll delve into learning concepts such as neural networks. We'll discuss neural networks (CNNs) recurrent neural networks (RNNs) and deep reinforcement learning. **Exploring Natural Language Processing (NLP)**; Lastly we will examine the field of natural language processing (NLP) and its significance, in AI research and applications. The course covers topics related to AI and ML including text processing, sentiment analysis, chatbots and language translation. We also delve into computer vision, which involves tasks like image processing, object detection, facial recognition and even generating images using GANs (Generative Adversarial Networks). Furthermore we explore applied AI and ML subjects such as robotics fundamentals covering robot motion planning and control. We also examine how AI and ML are employed in business domains like customer relationship management (CRM) financial modeling and market analysis. In addition to that we engage in discussions about the implications of AI technology including bias in machine learning models as well as the importance of AI governance. In terms of skills and tools covered in this course we focus on programming languages like Python and R for AI and ML development. We introduce students to data technologies such as Hadoop and Spark for handling large scale datasets. Moreover we explore cloud computing platforms like AWS, Azure or Google Cloud for deploying AI and ML models. Lastly we provide insights into project management methodologies to AI projects including Agile methodologies along with DevOps practices tailored for AI development. To conclude the course experience effectively while bridging theory with practice effectively through a capstone project where students can apply their acquired knowledge in a real world scenario or simulated environment. Additionally there is an opportunity, for internship experience where students can further consolidate their skills by working on hands on projects in industries.