B.Tech in CSE (AI & ML) + AME (DGCA) Syllabus

The B.Tech in Computer Science Engineering (AI & ML) + AME program offers a comprehensive curriculum designed to equip students with essential skills and knowledge in both information technology and aviation management. The key subjects include:

what you will study ?

B Tech in CSE (AI & ML) program

  • Programming Fundamentals

  • Data Structures and Algorithms

  • Database Management Systems

  • Software Engineering

  • Web Technologies

  • Computer Networks

  • Operating Systems

  • Artificial Intelligence

  • Machine Learning

  • Data Mining and Warehousing

  • Cloud Computing

  • Mobile Application Development

  • Internet of Things (IoT)

  • Cybersecurity

  • Human-Computer Interaction

  • Project Management

  • Digital Image Processing

  • Ethics in Technology

  • Innovation and Entrepreneurship

  • Capstone Project

Aircraft Maintenance Engineering Subjects (DGCA )

  • Aircraft Maintenance Engineering Fundamentals

  • Aviation Regulations and Safety

  • Aircraft Structures

  • Aircraft Systems and Components

  • Power Plant and Propulsion Systems

  • Electrical Systems and Equipment

  • Instruments and Avionics

  • Aerodynamics and Flight Mechanics

  • Materials and Processes

  • Maintenance Practices and Procedures

  • Human Factors in Aviation

  • Environmental Control Systems

  • Fuel and Oil Systems

  • Aircraft Performance and Weight Balance

  • Inspection and Quality Control

  • Basic Aeronautical Engineering

  • Air Navigation and Communication Systems

  • Emergency Procedures and Safety Management

  • Practical Training and Workshops

  • Project Work and Case Studies

Semester-wise Core Subjects

Year 1: Basics of Aircraft Maintenance

Semester 1

Module 1: Aircraft Rules and Regulations (Civil Aviation Requirements - CAR)

  • Overview of DGCA regulations
  • Aviation law and safety protocols
  • Airworthiness requirements

Module 2: Basic Aircraft Maintenance Practices

  • Workshop practices and safety
  • Use of tools, equipment, and machines in maintenance
  • Introduction to aircraft systems and components

Module 3: Basic Aerodynamics

  • Principles of flight
  • Lift, drag, thrust, and weight balance
  • Aircraft stability and control

Module 4: Aircraft Materials and Hardware

  • Materials used in aircraft manufacturing
  • Types of fasteners, bearings, and seals
  • Corrosion detection and prevention

Module 5: Electrical Fundamentals

  • Basic electrical theory and applications
  • Circuit theory and aircraft electrical systems
  • Battery maintenance and power distribution systems

Module 6: Digital Techniques in Aircraft Systems

  • Digital systems in modern aircraft
  • Introduction to avionics and aircraft instruments
  • Software and digital systems maintenance

Semester 2

Module 7: Aircraft Propulsion (Turbine and Piston Engines)

  • Fundamentals of gas turbine and piston engines
  • Engine components and their functions
  • Engine maintenance procedures

Module 8: Aircraft Structures and Systems

  • Airframe structure types and materials
  • Hydraulic, pneumatic, and landing gear systems
  • Aircraft flight controls and fuel systems

Module 9: Basic Avionics Systems

  • Communication, navigation, and surveillance systems
  • Aircraft instrumentation and electronic flight systems
  • Maintenance and troubleshooting of avionics

Module 10: Aircraft Electrical and Electronic Systems

  • Power generation, distribution, and storage in aircraft
  • Wiring and connectors
  • Electronic system troubleshooting

Module 11: Human Factors in Aviation Maintenance

  • Human error and safety
  • Teamwork and communication in aviation
  • Maintenance environment and ergonomics

Module 12: Aircraft Maintenance Documentation

  • Logbook entries and technical documentation
  • Maintenance schedules and records
  • Compliance with airworthiness directives

Year 2: Specialized Aircraft Maintenance Training

Semester 3

Module 13: Airframe and Engine Inspection Techniques

  • Procedures for inspecting airframes and engines
  • Non-destructive testing (NDT) methods
  • Aircraft defect analysis and repair techniques

Module 14: Advanced Avionics and Electronics

  • Maintenance of advanced avionics systems
  • Flight management and autopilot systems
  • Digital aircraft systems and software updates

Module 15: Aircraft Maintenance Safety Procedures

  • Safety management systems (SMS)
  • Accident investigation and reporting
  • Emergency procedures and fire safety in aviation

Module 16: Aircraft Powerplant Maintenance

  • Advanced study of aircraft engines (turbine and piston)
  • Engine testing, calibration, and performance assessment
  • Engine removal, installation, and overhaul procedures

Module 17: Aircraft Electrical Wiring and Systems

  • Detailed wiring system maintenance
  • Electrical component maintenance and troubleshooting
  • Advanced electrical circuit analysis

Semester 4

Module 18: Air Regulations and Licensing Requirements

  • Detailed study of DGCA air regulations and licensing
  • Requirements for aircraft certification and release to service
  • Understanding aircraft certificates and flight releases

Module 19: Practical Training on Aircraft Systems

  • Hands-on training in actual aircraft maintenance environments
  • Aircraft line maintenance, base maintenance, and troubleshooting
  • Documentation of maintenance tasks for DGCA licensing

Module 20: Internship and Industry Exposure

  • On-the-job training with airlines, MROs (Maintenance, Repair, and Overhaul), or aviation workshops
  • Real-time experience with aircraft maintenance and repair procedures
  • Reporting and evaluation as part of the DGCA module clearance

Module 21: Comprehensive DGCA Module Exams

  • Final examinations on all modules covered during the course
  • Practical and theoretical assessments to qualify for AME License
  • DGCA-approved examination for license issuance based on module clearances

B.Tech in CSE (AI & ML) Subjects

Semester 1

  1. Engineering Mathematics I
  2. Programming Fundamentals (C/C++)
  3. Physics for Engineers
  4. Chemistry for Engineers
  5. Communication Skills
  6. Computer Science Engineering Fundamentals
  7. Workshop Practice

Semester 2

  1. Engineering Mathematics II
  2. Data Structures and Algorithms
  3. Discrete Mathematics
  4. Digital Logic Design
  5. Computer Organization and Architecture
  6. Software Engineering Principles
  7. Environmental Science

Semester 3

  1. Engineering Mathematics III
  2. Database Management Systems
  3. Operating Systems
  4. Theory of Computation
  5. Object-Oriented Programming (Java)
  6. Data Communication and Networking
  7. Elective I (e.g., Cloud Computing, Web Technologies)

Semester 4

  1. Engineering Mathematics IV
  2. Design and Analysis of Algorithms
  3. Software Testing and Quality Assurance
  4. Compiler Design
  5. Microprocessors and Microcontrollers
  6. Human-Computer Interaction
  7. Elective II (e.g., Mobile Application Development, Internet of Things)

Semester 5

  1. Artificial Intelligence
  2. Machine Learning
  3. Computer Vision
  4. Big Data Analytics
  5. Artificial Neural Networks
  6. Information Security
  7. Elective III (e.g., Blockchain Technology, Robotics)

Semester 6

  1. Deep Learning
  2. Natural Language Processing
  3. Reinforcement Learning
  4. AI Ethics and Society
  5. Cloud Computing
  6. Research Methodology
  7. Elective IV (e.g., Advanced Database Systems, Data Warehousing)

Semester 7

  1. Capstone Project/Industrial Training
  2. Emerging Technologies
  3. Professional Ethics and Cyber Law
  4. Distributed Systems
  5. Elective V (e.g., Data Mining, Smart Systems)
  6. Elective VI (e.g., Augmented Reality, Virtual Reality)

Semester 8

  1. Major Project/Thesis
  2. Entrepreneurship and Innovation
  3. Advanced Topics in AI & ML
  4. Elective VII (e.g., Quantum Computing, Edge Computing)
  5. Elective VIII (e.g., Advanced Cybersecurity, Social Network Analysis)

B.Tech in CSE (AI & ML) + AME (DGCA) Projects

B.Tech in CSE (AI & ML) Projects

  • Chatbot Development

    Create an AI-powered chatbot for customer service or educational purposes using natural language processing (NLP) techniques.
  • Image Recognition System
    Develop a project that uses convolutional neural networks (CNNs) to classify and recognize images in various categories, such as animals or vehicles.

  • Sentiment Analysis Tool
    Build a sentiment analysis application that analyzes social media posts or reviews to determine public opinion about a specific topic or product.

  • Predictive Analytics for Stock Prices
    Use historical stock price data and machine learning algorithms to predict future stock prices and trends.

  • Recommendation System
    Create a recommendation engine for movies, books, or products based on user preferences and behavior using collaborative filtering or content-based filtering.

  • Speech Recognition System
    Implement a system that converts spoken language into text, utilizing deep learning techniques for accurate transcription.

  • Fraud Detection System
    Develop an AI-based system to detect fraudulent transactions in banking or e-commerce using anomaly detection techniques.

  • Smart Home Automation
    Build a smart home application that utilizes AI to automate household tasks based on user preferences and habits.

  • Autonomous Vehicle Simulation
    Create a simulation environment for autonomous vehicles, using machine learning to navigate and make driving decisions.

  • Health Monitoring System
    Develop an AI-based health monitoring application that tracks vital signs and predicts potential health issues based on historical data.

  • Optical Character Recognition (OCR)
    Build a project that converts scanned documents or images of text into editable text using machine learning algorithms.

  • Personal Finance Management App
    Create an application that utilizes AI to help users manage their finances, analyze spending patterns, and provide budget recommendations.

  • Disease Prediction System
    Develop a machine learning model that predicts the likelihood of diseases based on patient data and medical history.

  • Emotion Detection from Text
    Create a system that analyzes text data to detect emotions expressed by users, utilizing NLP techniques.

  • Virtual Assistant
    Build a virtual assistant application that can perform tasks such as setting reminders, answering questions, and providing information using voice commands.

AME (DGCA) Projects

  • Aircraft Maintenance Manual Development
    Create a comprehensive maintenance manual for a specific aircraft type, including maintenance schedules, procedures, and troubleshooting guides.

  • Safety Management System (SMS) Implementation
    Develop a project focusing on implementing a Safety Management System in an aviation organization, outlining processes for risk assessment and safety reporting.

  • Aircraft Performance Analysis
    Conduct an analysis of an aircraft's performance metrics, including takeoff and landing distances, fuel efficiency, and weight calculations.

  • Component Overhaul Procedure
    Design a detailed procedure for the overhaul of a specific aircraft component (e.g., landing gear, engine) based on regulatory standards.

  • Avionics Systems Integration
    Develop a project that focuses on the integration of avionics systems, including navigation, communication, and flight control systems, into an aircraft.

  • Maintenance Tracking System
    Create a digital system for tracking maintenance schedules, repairs, and inspections for aircraft, ensuring compliance with regulatory requirements.

  • Inspection Checklist Development
    Develop a standardized checklist for pre-flight, post-flight, and periodic inspections of aircraft systems and components.

  • Aircraft Ground Support Equipment (GSE) Analysis
    Conduct a study on the various types of ground support equipment used in aircraft maintenance and their impact on operational efficiency.

  • Environmental Impact Assessment
    Analyze the environmental impact of aircraft maintenance activities and propose measures for sustainable practices within maintenance facilities.

  • Human Factors in Aviation Maintenance
    Research and present findings on the role of human factors in aviation maintenance, including training, communication, and error management.

  • Composite Material Repair Techniques
    Develop a project that explores the techniques and methodologies for repairing composite materials used in modern aircraft structures.

  • Airworthiness Directive (AD) Compliance
    Create a compliance plan for addressing airworthiness directives issued by aviation authorities, outlining procedures and timelines for implementation.

  • Emergency Response Planning
    Design an emergency response plan for aircraft incidents, detailing procedures for evacuations, fire suppression, and medical assistance.

  • Fuel System Inspection and Testing
    Conduct an analysis of fuel system components and develop inspection procedures for ensuring fuel system integrity and performance.

  • Innovations in Aircraft Maintenance Technology
    Research and present emerging technologies in aircraft maintenance, such as drones for inspections, predictive maintenance software, and augmented reality training tools.

Internships in B.Tech in CSE (AI & ML) + AME (DGCA)

Internships in the B.Tech in Computer Science Engineering (AI & ML) combined with Aircraft Maintenance Engineering (AME) programs are crucial for bridging the gap between theoretical knowledge and practical application. These internships provide students with opportunities to work on cutting-edge technology projects while gaining exposure to the aviation industry. Students can apply their skills in areas such as software development for aviation systems, data analysis for flight operations, and machine learning for predictive maintenance.

Why Internships Matter?

  • Practical Exposure: Gain hands-on experience in implementing AI algorithms, machine learning models, and maintenance procedures in real-world aviation contexts.

  • Skill Enhancement: Develop critical skills in programming, data analysis, and aircraft systems management while enhancing your technical and analytical capabilities.

  • Industry Mentorship: Work alongside experienced professionals in both IT and aviation, gaining insights into best practices and industry standards.

  • Problem Solving: Address real challenges in aviation maintenance and IT, improving your ability to analyze data and make informed decisions.

  • Networking Opportunities: Establish professional connections within both the IT and aviation sectors, which can lead to future job placements.

  • Career Clarity: Explore diverse roles in IT and aviation to better understand your career path and make informed decisions regarding future opportunities.

  • Market Readiness: Prepare for careers in both technology and aviation through hands-on experience that highlights your unique skill set in these rapidly evolving industries.

FAQs

What foundational skills will I develop in this course?

You will develop critical skills in programming, analytical thinking, and problem-solving, essential for success in the tech industry.

How does the course prepare me for a career in AI?

The curriculum focuses on both theoretical knowledge and practical experience, giving you exposure to real-world AI applications.

Will I have access to industry-standard tools and technologies?

Yes, the course includes training on tools commonly used in the industry, such as TensorFlow and AWS.

Are group projects a part of the curriculum?

Yes, group projects encourage collaboration and help you learn how to work effectively in teams.

How will this course enhance my coding skills?

Through continuous practice and assignments in various programming languages, you will significantly improve your coding abilities.

Is there an emphasis on research in this program?

Yes, students are encouraged to engage in research projects, particularly in emerging fields like AI and machine learning.

What kind of assignments can I expect?

You will have a mix of theoretical assignments, coding exercises, and hands-on projects that apply what you've learned.

How does the syllabus incorporate current industry trends?

The syllabus is regularly updated to reflect the latest advancements and trends in technology and AI.

Will I learn about the ethical implications of AI?

Yes, the program includes discussions on ethics, data privacy, and the societal impacts of AI technologies.

What role does data analytics play in this course?

Data analytics is a crucial part of the curriculum, helping you learn to interpret and derive insights from data.

Are there opportunities for internships during the course?

Yes, internships are often integrated into the program to provide you with hands-on experience in the industry.

Will I have the chance to work on a capstone project?

Yes, a capstone project is typically part of the final year, allowing you to showcase your skills on a significant project.

What industries can I work in after graduation?

Graduates can work in tech companies, finance, healthcare, and many other sectors that require AI expertise.

Is there support for job placement after graduation?

Yes, many institutions provide career services and job placement assistance to help students transition into the workforce.

What research areas can I explore during my studies?

You can explore areas such as machine learning algorithms, natural language processing, and robotics.

Will I learn about software development methodologies?

Yes, the course covers various software development methodologies to prepare you for real-world projects.

Are there guest lectures or industry interactions included?

Yes, many programs include guest lectures from industry professionals, providing insights into current trends and challenges.

How do I stay updated on new technologies while studying?

The course encourages self-directed learning and offers access to various educational resources. Staying engaged with online platforms, attending workshops, and participating in tech communities can help you keep up with advancements.

What skills are essential for succeeding in this program?

A strong interest in technology, problem-solving abilities, and a willingness to learn new programming languages are crucial for success. Additionally, good communication skills and the ability to work collaboratively will enhance your experience and outcomes in the program.

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