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B-TECH in Information Technology at Alliance University
Bengaluru, Karnataka
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About the Specialization
What is Information Technology at Alliance University Bengaluru?
This Information Technology program at Alliance University focuses on equipping students with expertise in cutting-edge computing technologies and applications. With a strong emphasis on practical skills and theoretical foundations, the curriculum addresses the evolving demands of the Indian IT industry, covering areas from software development to cybersecurity and data science. The program aims to foster innovation and problem-solving capabilities essential for future tech leaders.
Who Should Apply?
This program is ideal for aspiring engineers and innovators keen on a career in the dynamic IT sector. It attracts fresh 10+2 graduates with a strong aptitude for mathematics and science, seeking foundational knowledge in programming, databases, and networks. Additionally, it caters to individuals passionate about technology, eager to contribute to India''''s digital transformation, and looking for a structured pathway into software development, data analytics, or cybersecurity roles.
Why Choose This Course?
Graduates of this program can expect diverse India-specific career paths, including Software Engineer, Data Analyst, Network Administrator, Cybersecurity Specialist, and IT Consultant. Entry-level salaries typically range from INR 4-7 LPA, with experienced professionals earning significantly more. Growth trajectories are robust in Indian IT companies, driven by digital initiatives. The program also prepares students for global certifications like AWS, Microsoft Azure, and Cisco, enhancing their employability.
Student Success Practices
Foundation Stage
Master Programming Fundamentals- (Semester 1-2)
Dedicate significant time to understanding core programming concepts (like C, C++, OOP) and data structures. Practice daily coding challenges to build logic and problem-solving skills.
Tools & Resources
HackerRank, LeetCode, GeeksforGeeks, Alliance University coding clubs
Career Connection
Strong fundamentals are crucial for cracking coding interviews and excelling in initial software development roles at Indian tech companies.
Develop Strong Academic Habits- (Semester 1-2)
Focus on conceptual clarity in Engineering Mathematics and Physics. Form study groups with peers, attend all lectures, and actively participate in lab sessions to reinforce theoretical knowledge with practical application.
Tools & Resources
Class notes, textbooks, Khan Academy, NPTEL videos, peer study groups
Career Connection
A solid academic foundation ensures readiness for advanced technical subjects and demonstrates a strong learning aptitude to future employers.
Engage in Early Skill Building & Project Exploration- (Semester 1-2)
Beyond coursework, explore basic electronics kits, build small projects using Arduino/Raspberry Pi, or contribute to open-source initiatives. This hands-on experience fosters a maker mindset.
Tools & Resources
Arduino IDE, Raspberry Pi, GitHub, local electronics stores
Career Connection
Early projects showcase initiative and practical application of knowledge, making resumes stand out during internship applications.
Intermediate Stage
Gain Industry Exposure via Internships & Workshops- (Semester 3-5)
Actively seek short-term internships, attend industry workshops, and participate in hackathons. These experiences bridge academic learning with real-world industry practices.
Tools & Resources
Internshala, LinkedIn, university career services, company websites, local tech meetups
Career Connection
Internships are often a direct pathway to pre-placement offers, building a professional network and understanding corporate work culture in India.
Specialize through Electives & Certifications- (Semester 4-5)
Identify emerging areas like AI/ML, Cloud Computing, or Cybersecurity and choose program electives accordingly. Pursue online certifications to deepen expertise in your chosen specialization.
Tools & Resources
Coursera, Udemy, NPTEL, AWS/Azure/Google Cloud certification paths, specific vendor courses
Career Connection
Specialization makes you a more targeted candidate for specific roles in high-demand areas within the Indian IT job market, leading to better opportunities and salaries.
Build a Strong Professional Network- (Semester 3-5)
Connect with faculty, alumni, and industry professionals through university events, LinkedIn, and professional associations. Networking can open doors to mentorship and job opportunities.
Tools & Resources
LinkedIn, university alumni portal, industry conferences (e.g., Nasscom events), guest lectures
Career Connection
A robust professional network is invaluable for referrals, career advice, and discovering hidden job opportunities in India''''s competitive tech landscape.
Advanced Stage
Undertake Impactful Capstone Projects- (Semester 7-8)
Work on substantial, industry-relevant final year projects or research dissertations. Aim for innovative solutions to real-world problems, collaborating with peers or industry mentors.
Tools & Resources
University research labs, industry partners, faculty guidance, advanced development tools
Career Connection
A well-executed capstone project demonstrates your ability to apply comprehensive knowledge and problem-solving skills, significantly boosting your resume for top-tier placements.
Engage in Comprehensive Placement Preparation- (Semester 6-8)
Focus intensely on aptitude tests, technical interviews, group discussions, and mock interviews. Tailor your resume and portfolio to target specific companies and roles.
Tools & Resources
Placement cell resources, online aptitude platforms (e.g., Indiabix), mock interview panels, company-specific preparation materials
Career Connection
Thorough preparation is key to securing coveted positions in campus placements, especially with major Indian and multinational companies recruiting B.Tech IT graduates.
Cultivate Leadership and Soft Skills- (Semester 6-8)
Participate in leadership roles within student organizations, volunteer for university events, and practice public speaking and presentation skills. Soft skills are critical for career progression.
Tools & Resources
Toastmasters International, university clubs (e.g., entrepreneurship cells, debate clubs), workshops on communication
Career Connection
Beyond technical prowess, strong soft skills are highly valued by Indian employers for team collaboration, client interaction, and future leadership roles within organizations.
Program Structure and Curriculum
Eligibility:
- 10+2 or equivalent examination from a recognized Board with Physics and Mathematics as compulsory subjects along with one of the Chemistry/Biotechnology/Biology/Technical Vocational subject and obtained at least 45% marks (40% in case of candidate belonging to reserved category) in the above subjects taken together.
Duration: 8 semesters / 4 years
Credits: 160 Credits
Assessment: Internal: 50%, External: 50%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| AUBSM001 | Engineering Mathematics I | Core | 4 | Differential Calculus, Integral Calculus, Multivariable Calculus, Vector Calculus, Differential Equations |
| AUBPC001 | Engineering Physics | Core | 3 | Quantum Physics, Lasers and Fiber Optics, Solid State Physics, Electromagnetic Theory, Semiconductor Devices |
| AUBPC002 | Engineering Chemistry | Core | 3 | Electrochemistry, Polymers, Material Science, Water Technology, Corrosion |
| AUECM001 | Basic Electrical Engineering | Core | 3 | DC Circuits, AC Circuits, Transformers, Electrical Machines, Power Systems |
| AUECM002 | Engineering Graphics & Design | Core | 2 | Orthographic Projections, Isometric Projections, Sectional Views, CAD Tools, Assembly Drawings |
| AUMEC001 | Workshop/Manufacturing Practices | Lab | 1.5 | Fitting, Carpentry, Welding, Sheet Metal, Foundry |
| AUBPC003 | Engineering Physics Lab | Lab | 1 | Light Interference, Diffraction, Photoelectric Effect, Semiconductor Characteristics, Magnetic Fields |
| AUBPC004 | Engineering Chemistry Lab | Lab | 1 | Titrations, pH Metry, Conductometry, Viscosity Measurement, Spectroscopy |
| AUCSM001 | Programming for Problem Solving | Core | 3 | C Language Fundamentals, Control Structures, Functions, Arrays, Pointers, Structures |
| AUCSM002 | Programming for Problem Solving Lab | Lab | 1.5 | C Program Implementation, Debugging, Algorithmic Solutions, Data Handling, File Operations |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| AUBSM002 | Engineering Mathematics II | Core | 4 | Linear Algebra, Laplace Transforms, Fourier Series, Partial Differential Equations, Numerical Methods |
| AUECM003 | Basic Electronics Engineering | Core | 3 | Diodes and Rectifiers, Transistors, Amplifiers, Oscillators, Digital Logic Gates |
| AUCSM003 | Data Structures | Core | 3 | Arrays, Linked Lists, Stacks, Queues, Trees, Graphs, Sorting, Searching |
| AUCSM004 | Data Structures Lab | Lab | 1.5 | Data Structure Implementation, Algorithm Analysis, Problem Solving, Recursion, Memory Management |
| AUECM004 | Basic Electronics Engineering Lab | Lab | 1 | Diode Characteristics, Transistor Biasing, Amplifier Circuits, Logic Gate Implementation, Digital Circuits |
| AUHMC001 | English | Core | 2 | Communication Skills, Technical Writing, Public Speaking, Grammar, Vocabulary, Reading Comprehension |
| AUCSM005 | Object Oriented Programming | Core | 3 | OOP Concepts, Classes and Objects, Inheritance, Polymorphism, Abstraction, Encapsulation, Exception Handling |
| AUCSM006 | Object Oriented Programming Lab | Lab | 1.5 | C++ Program Design, Class Implementation, Object Creation, Inheritance Examples, Polymorphism Usage |
| AUBSS001 | Environmental Science | AECC | 0 | Ecosystems, Biodiversity, Pollution, Renewable Energy, Environmental Management |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| AUCSM007 | Discrete Mathematics | Core | 4 | Set Theory, Logic, Relations and Functions, Graph Theory, Combinatorics, Recurrence Relations |
| AUCSM008 | Database Management Systems | Core | 3 | Database Concepts, ER Model, Relational Model, SQL, Normalization, Transaction Management |
| AUCSM009 | Database Management Systems Lab | Lab | 1.5 | SQL Queries, Schema Design, Database Operations, PL/SQL, NoSQL Databases |
| AUCSM010 | Computer Organization and Architecture | Core | 3 | Computer System Basics, CPU Organization, Memory Hierarchy, I/O Organization, Pipelining, Instruction Sets |
| AUCSM011 | Operating Systems | Core | 3 | OS Concepts, Process Management, Memory Management, File Systems, I/O Systems, Deadlocks |
| AUCSM012 | Operating Systems Lab | Lab | 1.5 | Linux Commands, Shell Scripting, Process Scheduling, Memory Allocation, System Calls |
| AUCSM013 | Theory of Computation | Core | 3 | Finite Automata, Regular Expressions, Context-Free Grammars, Pushdown Automata, Turing Machines, Undecidability |
| AUDCC001 | Design and Analysis of Algorithms | Core | 3 | Algorithm Analysis, Asymptotic Notations, Divide and Conquer, Greedy Algorithms, Dynamic Programming, Graph Algorithms |
| AUDCC002 | Design and Analysis of Algorithms Lab | Lab | 1.5 | Algorithm Implementation, Time/Space Complexity Analysis, Problem Solving Strategies, Sorting, Searching |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| AUBSM003 | Probability & Statistics | Core | 4 | Probability Theory, Random Variables, Probability Distributions, Hypothesis Testing, Regression, Correlation |
| AUCSM014 | Computer Networks | Core | 3 | Network Topologies, OSI/TCP-IP Model, Data Link Layer, Network Layer, Transport Layer, Application Layer |
| AUCSM015 | Computer Networks Lab | Lab | 1.5 | Network Configuration, Socket Programming, Network Protocols, Packet Analysis, Network Security Tools |
| AUCSM016 | Software Engineering | Core | 3 | Software Development Life Cycle, Requirements Engineering, Design, Testing, Maintenance, Project Management |
| AUCSM017 | Compiler Design | Core | 3 | Lexical Analysis, Syntax Analysis, Semantic Analysis, Intermediate Code Generation, Code Optimization, Code Generation |
| AUPCC001 | Information Security | Core | 3 | Cryptography, Network Security, Application Security, Cyber Laws, Ethical Hacking, Security Policies |
| AUITPE001 | Program Elective - I (Example: Cloud Computing) | Elective | 3 | Cloud Models, Virtualization, Cloud Services (IaaS, PaaS, SaaS), Cloud Security, Big Data on Cloud |
| AUITPE002 | Program Elective - I Lab (Example: Cloud Computing Lab) | Lab | 1.5 | Cloud Platform Setup, Virtual Machine Deployment, Cloud Storage, Serverless Computing, Cloud APIs |
| AUHMC002 | Universal Human Values | AECC | 0 | Self-exploration, Human values, Ethics, Harmony, Professional ethics |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| AUCSM018 | Artificial Intelligence | Core | 3 | AI Fundamentals, Problem Solving, Knowledge Representation, Machine Learning, Expert Systems, Natural Language Processing |
| AUCSM019 | Artificial Intelligence Lab | Lab | 1.5 | Python for AI, Search Algorithms, Heuristics, Logic Programming, Machine Learning Libraries, Data Preprocessing |
| AUITPE003 | Program Elective - II (Example: Web Technologies) | Elective | 3 | HTML, CSS, JavaScript, Web Servers, Client-Server Architecture, Databases for Web, Web Frameworks |
| AUITPE004 | Program Elective - II Lab (Example: Web Technologies Lab) | Lab | 1.5 | Front-end Development, Back-end Development, API Integration, Database Connectivity, Web Security Implementation |
| AUITPE005 | Program Elective - III (Example: Data Mining) | Elective | 3 | Data Preprocessing, Classification, Clustering, Association Rule Mining, Regression, Anomaly Detection |
| AUITPE006 | Program Elective - III Lab (Example: Data Mining Lab) | Lab | 1.5 | Data Cleaning, Feature Engineering, Algorithm Implementation, Evaluation Metrics, Data Visualization |
| AUITE001 | Open Elective - I | Elective | 3 | Varies widely based on chosen elective (e.g., IoT, Blockchain, Entrepreneurship) |
| AUPRJ001 | Mini Project | Project | 2 | Project Planning, Design, Implementation, Testing, Documentation, Presentation |
| AUIET001 | Internship/Industrial Training | AECC | 2 | Industry Exposure, Practical Skill Application, Report Writing, Professional Networking |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| AUCSM020 | Machine Learning | Core | 3 | Supervised Learning, Unsupervised Learning, Reinforcement Learning, Neural Networks, Deep Learning Introduction, Model Evaluation |
| AUCSM021 | Machine Learning Lab | Lab | 1.5 | ML Libraries (Scikit-learn, TensorFlow), Data Analysis, Model Training, Hyperparameter Tuning, Visualization |
| AUITPE007 | Program Elective - IV (Example: Cyber Security Essentials) | Elective | 3 | Network Security, Cryptography, Incident Response, Digital Forensics, Risk Management, Security Audits |
| AUITPE008 | Program Elective - IV Lab (Example: Cyber Security Lab) | Lab | 1.5 | Network Scanning, Vulnerability Assessment, Penetration Testing Tools, Firewall Configuration, Intrusion Detection/Prevention Systems |
| AUITPE009 | Program Elective - V (Example: Big Data Analytics) | Elective | 3 | Hadoop Ecosystem, Apache Spark, NoSQL Databases, Data Warehousing, Data Streaming, Business Intelligence |
| AUITPE010 | Program Elective - V Lab (Example: Big Data Analytics Lab) | Lab | 1.5 | Hadoop Setup, MapReduce Programming, Spark Applications, Hive, Pig, Data Visualization Tools |
| AUITE002 | Open Elective - II | Elective | 3 | Varies widely based on chosen elective |
| AUPRJ002 | Minor Project / Case Study | Project | 2 | Research Methodology, Problem Definition, Solution Design, Prototyping, Evaluation, Report Writing |
| AUHSS001 | Professional Ethics & Intellectual Property Rights | AECC | 0 | Ethical Theories, Professionalism, IPR Laws, Patents, Copyrights, Trademarks, Cyber Ethics |
Semester 7
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| AUCSM022 | Distributed Computing | Core | 3 | Distributed Systems Concepts, Client-Server, Peer-to-Peer, Remote Procedure Calls, Message Passing, Distributed Transactions, Consensus Algorithms |
| AUCSM023 | Distributed Computing Lab | Lab | 1.5 | Socket Programming, Remote Method Invocation, Web Services, Distributed File Systems, Cloud API Usage, Docker/Kubernetes Basics |
| AUITPE011 | Program Elective - VI (Example: Internet of Things) | Elective | 3 | IoT Architecture, Sensors and Actuators, Communication Protocols (MQTT, CoAP), Edge Computing, IoT Security, Cloud Integration |
| AUITPE012 | Program Elective - VI Lab (Example: Internet of Things Lab) | Lab | 1.5 | Sensor Interfacing, Microcontroller Programming, Data Acquisition, Cloud Platform Connectivity, IoT Application Development |
| AUITE003 | Open Elective - III | Elective | 3 | Varies widely based on chosen elective |
| AUIET002 | Internship/Industrial Training | AECC | 2 | Advanced Industry Exposure, Project-Based Learning, Professional Skill Development, Career Planning |
| AUPRJ003 | Project Work / Dissertation | Project | 8 | Advanced Research, System Design, Large-Scale Implementation, Testing, Thesis Writing, Oral Defense |
Semester 8
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| AUITPE013 | Program Elective - VII (Example: Deep Learning) | Elective | 3 | Neural Network Architectures, Convolutional Neural Networks, Recurrent Neural Networks, Generative Models, Deep Learning Frameworks (TensorFlow/PyTorch) |
| AUITPE014 | Program Elective - VII Lab (Example: Deep Learning Lab) | Lab | 1.5 | Model Building, Training on Large Datasets, Hyperparameter Optimization, Transfer Learning, GPU Computing |
| AUITE004 | Open Elective - IV | Elective | 3 | Varies widely based on chosen elective |
| AUPRJ004 | Project Work / Dissertation | Project | 8 | Refinement of Project, Final Implementation, Comprehensive Testing, Thesis Finalization, Presentation to Panel |
