MSBTE K-Scheme Syllabus for AI And Machine Learning Diploma
MSBTE AI And Machine Learning Second Semester Syllabus (AN2K)
Download the AI And Machine Learning Second Semester Syllabus PDF using the link below.
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Looking to download the MSBTE AI and Machine Learning Second Semester Syllabus PDF as per the K Scheme? You’re at the right place! This page provides the official and latest AN2K syllabus PDF for the Second Semester of Artificial Intelligence and Machine Learning diploma course under the MSBTE (Maharashtra State Board of Technical Education).
The MSBTE AN2K syllabus PDF features core subjects such as Programming in C, Applied Mathematics, Basic Electronics, and Fundamentals of AI and ML. It also includes lab work, practical sessions, and skill-oriented learning activities. Students can access important academic details like subject codes, weekly teaching hours, course outcomes, and assessment patterns—perfect for exam preparation and academic planning.
Designed under the MSBTE K Scheme, this syllabus is tailored for AI and Machine Learning (AN) diploma students and helps strengthen the base for advanced topics in data science, algorithms, and machine learning.
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 AN2K syllabus
✅ Official MSBTE Second Semester syllabus under K Scheme
✅ Includes C programming, AI basics, and practical components
✅ Ideal for second-semester AI and Machine Learning diploma students
Click the link below to download the MSBTE AI and Machine Learning Second Semester syllabus PDF (AN2K) and stay ahead with the latest curriculum.
The second semester of the MSBTE AI and Machine Learning (AIML) diploma builds upon the foundational skills developed in the first semester. Under the K-Scheme curriculum, the AN2K semester introduces students to deeper scientific principles, improved mathematical reasoning, and essential computer engineering fundamentals that are crucial for understanding AI and ML concepts in later semesters. This semester acts as a bridge between basic engineering education and specialized AI-driven subjects such as Python programming, data handling, database concepts, statistics, and early machine learning logic. A clear understanding of the complete AN2K syllabus helps students plan their studies more effectively and prepare confidently for upcoming technical subjects.
The AN2K syllabus generally includes subjects such as Applied Mathematics, Applied Science, Engineering Graphics, Basic Electrical Engineering, Communication Skills, and Workshop Practice. Although these subjects appear common across engineering domains, they carry special significance for AIML students. Applied Mathematics in the second semester introduces concepts used heavily in algorithms, data models, optimization techniques, and statistical computations—core components of AI and machine learning. Being strong in mathematics allows students to analyze datasets, understand loss functions, derive formulas, and interpret algorithmic behavior more accurately.
Applied Science deepens a student’s understanding of scientific principles that relate to computing systems, materials, energy transfer, and electromagnetic concepts. These fundamentals become valuable when students later study AI hardware, embedded systems, robotics, IoT devices, and sensor-based technologies. Engineering Graphics enhances diagram interpretation, visualization skills, and technical drawing ability—skills that help students understand flowcharts, neural network diagrams, design frameworks, and AI system architecture.
Basic Electrical Engineering is an important addition in the second semester. It introduces students to electrical laws, circuits, power distribution, instrumentation, and safety practices. A good understanding of electrical concepts is essential for AIML students who will later work on AI hardware, GPU systems, robotic integration, automation equipment, and microcontroller-based projects.
Communication Skills in the second semester further enhances students’ professional communication abilities. AI and Machine Learning fields require clear documentation, structured reporting, and the ability to explain complex ideas in simple terms. This subject trains students to communicate effectively during projects, presentations, lab work, and technical documentation.
Workshop Practice strengthens hands-on skills by introducing students to tools, instruments, fabrication basics, and industrial safety. While AIML is largely a software-driven field, understanding physical tools and engineering practices adds value when students later work with robotics, drones, IoT devices, sensor networks, or AI-enabled hardware systems.
The AN2K K-Scheme syllabus includes detailed unit-wise content, practical components, learning outcomes, weekly hours, credits, and the assessment scheme for both theory and practical examinations. Understanding these details helps students manage their workload, prioritize important chapters, and prepare according to MSBTE exam patterns. Since future AIML subjects become intensely technical—from Python programming to machine learning algorithms—building a strong base in the second semester is essential.
At msbtesolutions.com, students can download the official MSBTE AI and Machine Learning Second Semester (AN2K) Syllabus PDF under the K-Scheme. The PDF contains all unit-wise syllabus details, course outcomes, term-work guidelines, and exam patterns in a clean, easy-to-understand layout suitable for students, teachers, and institutions.
If you are entering the second semester of the MSBTE AIML diploma, reviewing the AN2K syllabus will help you develop strong analytical, mathematical, scientific, and communication skills. These fundamentals are key to excelling in advanced subjects like Python Programming, Data Analytics, Machine Learning Fundamentals, Database Systems, and AI Development Tools in the coming semesters. Download the MSBTE AN2K Second Semester Syllabus PDF today and continue your AI and Machine Learning journey with clarity and confidence.
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