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Fees
₹12,00,000
Placement
92.0%
Avg Package
₹4,50,000
Highest Package
₹8,00,000
Fees
₹12,00,000
Placement
92.0%
Avg Package
₹4,50,000
Highest Package
₹8,00,000
Seats
120
Students
1,200
Seats
120
Students
1,200
The curriculum for the Vocational Training program at Scope Global Skills University Bhopal is meticulously designed to provide students with a comprehensive and practical education that aligns with industry requirements. The program is structured over eight semesters, with each semester building upon the previous one to ensure a progressive learning experience. The curriculum includes core courses, departmental electives, science electives, and laboratory sessions that are designed to foster both theoretical understanding and practical application.
| SEMESTER | COURSE CODE | COURSE TITLE | CREDIT STRUCTURE (L-T-P-C) | PREREQUISITES |
|---|---|---|---|---|
| 1 | ENG101 | English Communication | 3-0-0-3 | - |
| 1 | MAT101 | Calculus I | 4-0-0-4 | - |
| 1 | PHY101 | Physics I | 3-0-0-3 | - |
| 1 | CHM101 | Chemistry I | 3-0-0-3 | - |
| 1 | EG101 | Engineering Graphics | 2-0-0-2 | - |
| 1 | CS101 | Introduction to Programming | 2-0-2-3 | - |
| 1 | EC101 | Electrical Circuits | 3-0-0-3 | - |
| 2 | MAT102 | Calculus II | 4-0-0-4 | MAT101 |
| 2 | PHY102 | Physics II | 3-0-0-3 | PHY101 |
| 2 | CHM102 | Chemistry II | 3-0-0-3 | CHM101 |
| 2 | CS102 | Data Structures and Algorithms | 3-0-2-4 | CS101 |
| 2 | EC102 | Electronics Fundamentals | 3-0-0-3 | - |
| 2 | ME101 | Mechanics of Materials | 3-0-0-3 | - |
| 2 | EN101 | Engineering Ethics | 2-0-0-2 | - |
| 3 | MAT201 | Statistics and Probability | 3-0-0-3 | MAT102 |
| 3 | PHY201 | Thermodynamics | 3-0-0-3 | PHY102 |
| 3 | CHM201 | Organic Chemistry | 3-0-0-3 | CHM102 |
| 3 | CS201 | Database Management Systems | 3-0-2-4 | CS102 |
| 3 | EC201 | Signals and Systems | 3-0-0-3 | EC102 |
| 3 | ME201 | Fluid Mechanics | 3-0-0-3 | ME101 |
| 3 | EN201 | Project Management | 2-0-0-2 | - |
| 4 | MAT202 | Linear Algebra | 3-0-0-3 | MAT201 |
| 4 | PHY202 | Quantum Physics | 3-0-0-3 | PHY201 |
| 4 | CHM202 | Inorganic Chemistry | 3-0-0-3 | CHM201 |
| 4 | CS202 | Operating Systems | 3-0-2-4 | CS201 |
| 4 | EC202 | Digital Electronics | 3-0-0-3 | EC201 |
| 4 | ME202 | Heat Transfer | 3-0-0-3 | ME201 |
| 4 | EN301 | Entrepreneurship | 2-0-0-2 | - |
| 5 | CS301 | Machine Learning | 3-0-2-4 | CS202 |
| 5 | EC301 | Communication Systems | 3-0-0-3 | EC202 |
| 5 | ME301 | Manufacturing Processes | 3-0-0-3 | ME202 |
| 5 | EN401 | Research Methodology | 2-0-0-2 | - |
| 5 | CS302 | Web Development | 3-0-2-4 | CS202 |
| 5 | EC302 | Microprocessors | 3-0-0-3 | EC202 |
| 5 | ME302 | Design of Machine Elements | 3-0-0-3 | ME301 |
| 6 | CS401 | Artificial Intelligence | 3-0-2-4 | CS301 |
| 6 | EC401 | Antenna Engineering | 3-0-0-3 | EC301 |
| 6 | ME401 | Automotive Engineering | 3-0-0-3 | ME302 |
| 6 | EN501 | Capstone Project | 2-0-0-2 | - |
| 6 | CS402 | Mobile Applications | 3-0-2-4 | CS302 |
| 6 | EC402 | Embedded Systems | 3-0-0-3 | EC302 |
| 6 | ME402 | Industrial Engineering | 3-0-0-3 | ME401 |
| 7 | CS501 | Advanced Data Science | 3-0-2-4 | CS401 |
| 7 | EC501 | Optical Communication | 3-0-0-3 | EC401 |
| 7 | ME501 | Robotics | 3-0-0-3 | ME402 |
| 7 | EN601 | Project Planning | 2-0-0-2 | - |
| 7 | CS502 | Cloud Computing | 3-0-2-4 | CS402 |
| 7 | EC502 | Power Electronics | 3-0-0-3 | EC402 |
| 7 | ME502 | Advanced Manufacturing | 3-0-0-3 | ME501 |
| 8 | CS601 | Deep Learning | 3-0-2-4 | CS501 |
| 8 | EC601 | Wireless Networks | 3-0-0-3 | EC501 |
| 8 | ME601 | Advanced Thermodynamics | 3-0-0-3 | ME502 |
| 8 | EN701 | Final Year Project | 2-0-0-2 | - |
| 8 | CS602 | Blockchain Technology | 3-0-2-4 | CS502 |
| 8 | EC602 | RF Engineering | 3-0-0-3 | EC502 |
| 8 | ME602 | Advanced Control Systems | 3-0-0-3 | ME601 |
The departmental elective courses in the Vocational Training program are designed to provide students with in-depth knowledge and specialized skills in their chosen fields. These courses are offered in the later semesters and are tailored to meet the evolving demands of the industry. The following are some of the advanced departmental elective courses offered in the program:
This course provides students with a comprehensive understanding of machine learning algorithms and their applications. Students learn about supervised and unsupervised learning techniques, neural networks, deep learning, and reinforcement learning. The course emphasizes practical implementation through hands-on projects and real-world datasets. Students are expected to have a strong foundation in mathematics and programming to succeed in this course.
The Artificial Intelligence course explores the fundamental concepts and techniques used in creating intelligent systems. Students study topics such as search algorithms, knowledge representation, planning, and natural language processing. The course includes practical components where students develop AI applications using modern frameworks and tools. This course prepares students for advanced roles in AI research and development.
This course delves into advanced data science techniques and their applications in various domains. Students learn about big data analytics, data visualization, and predictive modeling. The course covers advanced statistical methods and machine learning algorithms used in data science. Students work on real-world projects that involve data analysis and interpretation using industry-standard tools.
The Deep Learning course provides students with an in-depth understanding of neural network architectures and their applications. Students study convolutional neural networks, recurrent neural networks, and transformers. The course includes practical implementation of deep learning models using frameworks like TensorFlow and PyTorch. Students are expected to have a strong foundation in mathematics and programming to succeed in this course.
This course covers the principles and techniques of communication systems. Students learn about modulation techniques, noise analysis, and error correction methods. The course includes practical components where students design and test communication systems. Students are expected to have a strong foundation in electronics and signal processing to succeed in this course.
The Antenna Engineering course explores the design and analysis of antennas for various applications. Students study different types of antennas, radiation patterns, and impedance matching techniques. The course includes practical components where students design and test antenna systems. Students are expected to have a strong foundation in electromagnetic theory to succeed in this course.
This course covers the principles and techniques of optical communication systems. Students learn about fiber optic transmission, optical amplifiers, and wavelength division multiplexing. The course includes practical components where students work with optical communication equipment. Students are expected to have a strong foundation in electronics and optics to succeed in this course.
The Wireless Networks course explores the design and analysis of wireless communication networks. Students study wireless protocols, network topologies, and quality of service. The course includes practical components where students design and test wireless networks. Students are expected to have a strong foundation in networking and signal processing to succeed in this course.
This course covers the principles and techniques of manufacturing processes. Students learn about casting, forming, machining, and joining processes. The course includes practical components where students work with manufacturing equipment. Students are expected to have a strong foundation in materials science and engineering to succeed in this course.
The Automotive Engineering course explores the design and analysis of automotive systems. Students study engine performance, vehicle dynamics, and safety systems. The course includes practical components where students work on automotive projects. Students are expected to have a strong foundation in mechanical engineering and materials science to succeed in this course.
This course covers the principles and techniques of robotics. Students learn about robot kinematics, control systems, and sensor integration. The course includes practical components where students design and build robotic systems. Students are expected to have a strong foundation in mechanical and electrical engineering to succeed in this course.
The Advanced Thermodynamics course explores the principles and applications of thermodynamics in advanced systems. Students study thermodynamic cycles, heat transfer, and energy conversion. The course includes practical components where students analyze and design thermodynamic systems. Students are expected to have a strong foundation in thermodynamics and heat transfer to succeed in this course.
The department's philosophy on project-based learning is rooted in the belief that students learn best when they are actively engaged in solving real-world problems. This approach is designed to foster critical thinking, creativity, and collaboration among students. The program emphasizes hands-on learning experiences that bridge the gap between theoretical knowledge and practical application.
Mini-projects are an integral part of the curriculum and are designed to provide students with early exposure to practical problem-solving. These projects are typically completed in the second and third years of the program and are structured to be manageable yet challenging. Students work in teams to address specific technical challenges, allowing them to develop teamwork and communication skills.
The evaluation criteria for mini-projects include the technical feasibility of the solution, the clarity of documentation, and the effectiveness of the presentation. Students are expected to demonstrate their understanding of the underlying concepts and their ability to apply them in practical scenarios.
The final-year thesis/capstone project is the culmination of the students' academic journey and is designed to showcase their comprehensive understanding of their field. This project is typically completed in the eighth semester and involves extensive research and development.
Students are required to select a project topic in consultation with their faculty mentor and submit a detailed project proposal. The project must demonstrate originality, technical depth, and practical relevance. The evaluation criteria for the capstone project include the quality of research, the innovation of the solution, the clarity of documentation, and the effectiveness of the presentation.
Faculty mentors play a crucial role in guiding students through the project process. They provide technical expertise, resources, and support throughout the project lifecycle. The mentorship process is designed to be collaborative, with faculty members working closely with students to ensure their success.
Students select their projects based on their interests, career aspirations, and the availability of faculty mentors. The selection process involves a detailed proposal submission and review by the departmental committee. Projects are chosen to ensure a diverse range of topics and to align with industry needs and research priorities.
