MSBTE K-Scheme Syllabus for AI And Machine Learning Diploma
Note: The subjects listed for the 6th semester are provisional and not yet finalized. Updates will be made once the official MSBTE syllabus is confirmed. Please check back soon for the latest information.
MSBTE AI And Machine Learning Sixth Semester Syllabus (AN6K)
Download the AI And Machine Learning Sixth Semester Syllabus PDF using the link below.
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Looking for the MSBTE AI and Machine Learning Sixth Semester Syllabus PDF under the K Scheme? You’ve come to the right place! This page provides the official and updated AN6K syllabus PDF for the Sixth Semester of the Artificial Intelligence and Machine Learning diploma course under MSBTE (Maharashtra State Board of Technical Education).
The MSBTE AN6K syllabus PDF includes industry-focused subjects such as AI System Design, Advanced Machine Learning Techniques, AI Ethics, and Final Project Work, offering a perfect blend of theoretical knowledge and practical application. It also features essential academic details such as subject codes, weekly lecture/practical hours, course outcomes, and assessment methods to help students stay organized and prepared for the semester.
Designed specifically for AI and Machine Learning (AN) diploma students, this syllabus follows the latest MSBTE K Scheme, emphasizing real-world AI applications and preparing students for professional challenges in the field.
In addition to core subjects, students enrolled in the MSBTE K-Scheme Computer Engineering Diploma will have the option to choose electives based on their interests and career goals. The availability of elective subjects may vary across different colleges and institutes.
✅ Free PDF download of AN6K syllabus
✅ Official MSBTE Sixth Semester syllabus under K Scheme
✅ Includes AI system design, advanced machine learning, ethics, and project work
✅ Ideal for AI and Machine Learning diploma students ready for industry challenges
Click the link below to download the MSBTE AI and Machine Learning Sixth Semester syllabus PDF (AN6K) and finish your diploma with the most up-to-date academic content.
The sixth semester of the MSBTE AI and Machine Learning (AIML) diploma is the final and most industry-oriented phase of the entire program. Under the K-Scheme curriculum, the AN6K semester focuses on advanced AI concepts, real-world project development, deployment techniques, data engineering practices, and professional skills required for entering the modern IT and AI job market. This semester is designed to ensure that students not only understand AI theory but can also apply it effectively in practical, real-life scenarios. Since this is the last academic semester, having a clear understanding of the complete AN6K syllabus helps students prepare thoroughly for final MSBTE examinations, portfolios, project work, and industry placements.
The AN6K syllabus typically includes core subjects such as Artificial Neural Networks (ANN), Big Data Analytics, AI Project Lifecycle & Deployment, Reinforcement Learning Basics, Cybersecurity for AI Systems, and the Major Project. Each subject helps students develop higher-level AI skills, making them job-ready for roles such as ML Engineer, AI Developer, Data Analyst, Big Data Engineer, Automation Developer, or Research Assistant.
Artificial Neural Networks (ANN) forms the backbone of modern deep learning. Students learn perceptrons, multi-layer networks, activation functions, backpropagation, optimization techniques, overfitting control, and advanced architectures such as CNNs, RNNs, LSTMs, and transformers. These concepts are essential for AI roles involving image processing, NLP, speech recognition, and predictive modeling.
Big Data Analytics introduces students to large-scale data processing tools and frameworks such as Hadoop, Spark, distributed databases, data pipelines, clustering methods, and scalable storage systems. With AI systems relying heavily on massive datasets, these skills are in high demand across industries like finance, healthcare, retail, telecommunications, and e-commerce.
AI Project Lifecycle & Deployment focuses on transforming machine learning models into deployable products. Students learn MLOps concepts, model training workflows, validation, containerization (Docker), API deployment, cloud integration, scalability, and monitoring techniques. This subject prepares students for real-world AI development environments where continuous integration, versioning, and automation are essential.
Reinforcement Learning Basics introduces decision-making models, reward systems, Q-learning, Markov decision processes, and basic RL algorithms. Reinforcement learning is widely used in robotics, automation, self-driving systems, gaming AI, and optimization engines.
Cybersecurity for AI Systems teaches students about threats, vulnerabilities, adversarial attacks, privacy concerns, and security protocols related to AI applications. As AI systems become more widely used, securing them from misuse and manipulation becomes increasingly important.
The Major Project is one of the key components of the AN6K semester. Students work on AI-based projects that may involve machine learning models, deep learning architectures, data analytics, cloud deployment, model optimization, or real-world problem solving. This project helps students build a strong portfolio that enhances their employability. It also improves teamwork, communication, documentation, and presentation skills.
The K-Scheme syllabus includes detailed unit-wise content, practical work, lab sessions, term-work requirements, project guidelines, and internal/external assessment patterns. Understanding this structure helps students manage their semester more effectively, focus on high-weightage units, and prepare strategically for MSBTE exams as well as project evaluations.
At msbtesolutions.com, students can download the official MSBTE AI and Machine Learning Sixth Semester (AN6K) Syllabus PDF under the K-Scheme. The PDF provides complete unit-wise details, course outcomes, project requirements, and assessment formats in a clean and easy-to-read layout.
If you are entering the final semester of the MSBTE AIML diploma, reviewing the AN6K syllabus will help you build advanced AI expertise, prepare for industry-level challenges, and complete your diploma journey with strong technical confidence. Download the MSBTE AN6K Sixth Semester Syllabus PDF today and take the next step toward becoming a skilled AI and Machine Learning professional.
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