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    Scholarships & exams

    support@collegese.com
    +91 88943 57155
    Pune, Maharashtra, India

    Duration

    4 Years

    Bachelor of Technology

    Iasscom Fortune Institute of Technology
    Duration
    4 Years
    Bachelor of Technology UG OFFLINE

    Duration

    4 Years

    Bachelor of Technology

    Iasscom Fortune Institute of Technology
    Duration
    Apply

    Fees

    ₹15,00,000

    Placement

    94.5%

    Avg Package

    ₹7,50,000

    Highest Package

    ₹20,00,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Bachelor of Technology
    UG
    OFFLINE

    Fees

    ₹15,00,000

    Placement

    94.5%

    Avg Package

    ₹7,50,000

    Highest Package

    ₹20,00,000

    Seats

    320

    Students

    3,200

    ApplyCollege

    Seats

    320

    Students

    3,200

    Curriculum

    Comprehensive Course Structure

    The Bachelor of Technology program at Iasscom Fortune Institute of Technology is structured over 8 semesters, each with a carefully curated blend of core subjects, departmental electives, science electives, and practical laboratory components. This structure ensures students build a robust foundation in fundamental sciences before progressing into specialized engineering disciplines.

    SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Pre-requisites
    1PHYS101Physics for Engineers3-1-0-4-
    1MATH101Calculus and Differential Equations4-0-0-4-
    1CHEM101Chemistry for Engineers3-1-0-4-
    1BIO101Introduction to Biology2-1-0-3-
    1CS101Programming Fundamentals2-0-2-4-
    1ENG101English Communication Skills2-0-0-2-
    1HSS101Social Sciences for Engineers2-0-0-2-
    2MATH201Linear Algebra and Probability3-0-0-3MATH101
    2PHYS201Electromagnetism and Optics3-1-0-4PHYS101
    2CHEM201Organic Chemistry3-1-0-4CHEM101
    2CS201Data Structures and Algorithms3-0-2-5CS101
    2MECH201Engineering Mechanics3-1-0-4-
    2ENG201Technical Writing2-0-0-2ENG101
    3MATH301Numerical Methods3-0-0-3MATH201
    3PHYS301Thermodynamics and Statistical Mechanics3-1-0-4PHYS201
    3CHEM301Physical Chemistry3-1-0-4CHEM201
    3CS301Database Management Systems3-0-2-5CS201
    3MECH301Mechanics of Materials3-1-0-4MECH201
    3CIVIL301Structural Analysis3-1-0-4-
    4MATH401Complex Variables and Transforms3-0-0-3MATH301
    4PHYS401Quantum Physics3-1-0-4PHYS301
    4CHEM401Chemical Kinetics3-1-0-4CHEM301
    4CS401Software Engineering3-0-2-5CS301
    4MECH401Mechanical Vibrations3-1-0-4MECH301
    4CIVIL401Transportation Engineering3-1-0-4CIVIL301
    5CS501Artificial Intelligence3-0-2-5CS401
    5MECH501Heat Transfer3-1-0-4MECH401
    5CIVIL501Geotechnical Engineering3-1-0-4CIVIL401
    5ELEC501Electromagnetic Fields3-1-0-4-
    6CS601Machine Learning3-0-2-5CS501
    6MECH601Control Systems3-1-0-4MECH501
    6CIVIL601Environmental Engineering3-1-0-4CIVIL501
    6ELEC601Digital Signal Processing3-1-0-4ELEC501
    7CS701Advanced Algorithms3-0-2-5CS601
    7MECH701Finite Element Analysis3-1-0-4MECH601
    7CIVIL701Construction Management3-1-0-4CIVIL601
    7ELEC701Embedded Systems3-1-0-4ELEC601
    8CS801Capstone Project0-0-6-12CS701
    8MECH801Final Year Thesis0-0-6-12MECH701
    8CIVIL801Project Management0-0-6-12CIVIL701
    8ELEC801Final Project0-0-6-12ELEC701

    Detailed Elective Course Descriptions

    Departmental electives play a pivotal role in shaping students' specialized expertise. Below are descriptions of advanced departmental courses:

    Course: Artificial Intelligence (CS501)
    Learning Objectives: This course introduces students to key concepts in AI, including knowledge representation, automated reasoning, machine learning techniques, and natural language processing. Students will implement AI models using Python frameworks like TensorFlow and PyTorch.

    Course: Machine Learning (CS601)
    Learning Objectives: Students will explore supervised and unsupervised learning algorithms, neural networks, deep learning architectures, and reinforcement learning principles. Practical applications include image recognition, recommendation systems, and predictive analytics.

    Course: Data Structures and Algorithms (CS201)
    Learning Objectives: This foundational course covers linear and non-linear data structures, algorithmic complexity analysis, sorting and searching techniques, graph algorithms, and dynamic programming. Students will implement solutions using C++ or Java.

    Course: Database Management Systems (CS301)
    Learning Objectives: Covers relational database design, SQL queries, normalization, transaction management, indexing, query optimization, and advanced topics like NoSQL databases and distributed systems.

    Course: Software Engineering (CS401)
    Learning Objectives: Students will learn software development lifecycle models, agile methodologies, requirement analysis, system design principles, testing strategies, and project management practices.

    Course: Heat Transfer (MECH501)
    Learning Objectives: This course focuses on conduction, convection, and radiation heat transfer mechanisms. Students will analyze thermal systems, solve problems involving heat exchangers, and design energy-efficient components.

    Course: Control Systems (MECH601)
    Learning Objectives: Covers open-loop and closed-loop control systems, transfer functions, block diagram reduction, stability analysis, root locus, and frequency response methods. Students will simulate system behavior using MATLAB/Simulink.

    Course: Environmental Engineering (CIVIL601)
    Learning Objectives: Focuses on water treatment processes, waste management systems, air pollution control, noise reduction techniques, and sustainable engineering practices in environmental contexts.

    Course: Embedded Systems (ELEC701)
    Learning Objectives: Introduces microcontroller architecture, embedded C programming, real-time operating systems, sensor integration, communication protocols, and IoT-based applications using ARM Cortex-M series processors.

    Course: Finite Element Analysis (MECH701)
    Learning Objectives: Students will learn finite element methods for structural, thermal, and fluid dynamics problems. They will use commercial software like ANSYS to solve engineering challenges.

    Project-Based Learning Philosophy

    The Department of Technology at Iasscom Fortune Institute of Technology strongly advocates for project-based learning as a means of fostering critical thinking, creativity, and practical application of knowledge. Our philosophy centers around experiential education where students work in teams to address real-world engineering problems.

    Mini-projects are assigned during the third and fourth semesters, allowing students to apply concepts learned in class to tangible projects. These projects are typically completed within 4–6 weeks and involve iterative design cycles, prototyping, documentation, and presentation skills development.

    The final-year thesis or capstone project is a comprehensive endeavor that spans the entire eighth semester. Students select their research topic under faculty mentorship, conduct literature reviews, perform experiments or simulations, analyze results, and present findings to an expert panel. Projects often lead to patents, publications, or industry partnerships.

    Project selection involves a structured process where students submit proposals detailing problem statements, objectives, methodology, timeline, and expected outcomes. Faculty members review these proposals and assign mentors based on expertise alignment and student interest.