.png&w=1920&q=75)
B-TECH in Information Technology Data Analytics Ibm at Alliance University
Bengaluru, Karnataka
.png&w=1920&q=75)
About the Specialization
What is Information Technology – Data Analytics (IBM) at Alliance University Bengaluru?
This Information Technology – Data Analytics specialization at Alliance University focuses on equipping students with advanced skills in data handling, processing, analysis, and visualization. It addresses the significant demand in the Indian industry for professionals capable of transforming raw data into actionable insights, driving business decisions. The program emphasizes both foundational IT knowledge and specialized data analytics techniques, preparing graduates for a rapidly evolving data-driven landscape.
Who Should Apply?
This program is ideal for fresh graduates passionate about technology and numbers, seeking entry into data science, business intelligence, or analytics roles. It also suits working professionals aiming to upskill in cutting-edge data technologies or career changers looking to transition into the booming data analytics sector in India. Candidates with strong analytical aptitude and a keen interest in problem-solving through data will thrive.
Why Choose This Course?
Graduates of this program can expect diverse career paths in India, including Data Analyst, Business Intelligence Developer, Machine Learning Engineer, and Data Scientist. Entry-level salaries typically range from INR 4-7 LPA, growing significantly with experience to INR 10-25+ LPA for mid to senior roles. The curriculum aligns with requirements for professional certifications like IBM Data Science Professional Certificate and various cloud data certifications, enhancing growth trajectories in Indian and multinational companies.
Student Success Practices
Foundation Stage
Master Programming Fundamentals in Python/Java- (Semester 1-2)
Dedicate significant time to hands-on coding in Python or Java, focusing on data structures, algorithms, and object-oriented programming. Build small projects to solidify understanding.
Tools & Resources
HackerRank, GeeksforGeeks, CodeChef, LeetCode, Official Python/Java documentation
Career Connection
Strong programming fundamentals are non-negotiable for any IT role, especially in data analytics, enabling efficient data manipulation and algorithm implementation during placements.
Develop Strong Mathematical & Statistical Foundation- (Semester 1-3)
Focus on understanding the core concepts of engineering mathematics, probability, and statistics. Practice problem-solving rigorously, as these form the bedrock for advanced data analytics.
Tools & Resources
Khan Academy, NPTEL courses (Probability and Statistics), Textbooks for Engineering Math
Career Connection
A solid quantitative aptitude is crucial for comprehending machine learning algorithms, statistical modeling, and data interpretation, highly valued in data science roles.
Engage in Peer Learning and Technical Clubs- (Semester 1-3)
Actively participate in study groups and join technical clubs related to coding or data. Collaborate on mini-projects, discuss complex topics, and attend workshops organized by peers or faculty.
Tools & Resources
College''''s technical clubs, GitHub for collaborative projects, Discord/WhatsApp study groups
Career Connection
Enhances problem-solving, teamwork, and communication skills, which are critical for group projects in academics and essential for corporate environments during internships and job roles.
Intermediate Stage
Build a Portfolio of Data-Centric Projects- (Semester 3-5)
Start working on personal data analysis projects using real-world datasets. Implement concepts learned in DBMS, Data Structures, and introductory ML. Focus on end-to-end data pipelines.
Tools & Resources
Kaggle datasets, Google Colab/Jupyter Notebooks, GitHub for project hosting, Tableau Public/Power BI
Career Connection
A strong project portfolio demonstrates practical skills and problem-solving abilities to recruiters, significantly boosting chances for internships and job placements in data analytics firms.
Acquire SQL and Database Proficiency- (Semester 4-5)
Master SQL for database querying and manipulation. Understand relational database concepts, normalization, and perform hands-on exercises with various database systems.
Tools & Resources
SQLZoo, LeetCode SQL problems, MySQL/PostgreSQL, Online courses on Udemy/Coursera
Career Connection
SQL is fundamental for almost all data-related roles. Proficiency in database management is a critical skill directly sought by Indian companies hiring for data analyst and data engineer positions.
Explore Data Visualization and Reporting Tools- (Semester 5-6)
Familiarize yourself with popular data visualization tools like Tableau or Power BI. Practice creating interactive dashboards and insightful reports from complex datasets.
Tools & Resources
Tableau Public (free), Microsoft Power BI Desktop (free), YouTube tutorials, Data Visualization best practices blogs
Career Connection
Effective data visualization is key for communicating insights. This skill is highly valued in business intelligence and data analyst roles, directly impacting career progression.
Advanced Stage
Undertake Industry Internships and Live Projects- (Semester 6-7)
Actively seek and complete internships with companies, focusing on data analytics, machine learning, or big data roles. Participate in college-provided live industry projects to gain practical exposure.
Tools & Resources
College Placement Cell, LinkedIn, Internshala, Company career pages
Career Connection
Internships provide invaluable real-world experience, build industry networks, and often lead to pre-placement offers, significantly easing the transition into full-time employment.
Specialize in Machine Learning/Deep Learning Frameworks- (Semester 6-8)
Delve deeper into machine learning and deep learning, mastering frameworks like Scikit-learn, TensorFlow, or PyTorch. Implement advanced models and understand their deployment aspects.
Tools & Resources
Coursera Specializations, DeepLearning.AI courses, Official framework documentation, Kaggle Competitions
Career Connection
Advanced ML/DL skills are in high demand for roles like ML Engineer, AI Scientist, and Advanced Data Analyst, commanding higher salaries in the Indian tech market.
Prepare for Placements and Technical Interviews- (Semester 7-8)
Practice aptitude, logical reasoning, and verbal ability tests. Focus on coding interview questions, data science case studies, and behavioral interview preparation specifically for data roles.
Tools & Resources
Placement training materials, Mock interviews, Glassdoor for company-specific interview questions, Books on Data Science Interviews
Career Connection
Thorough preparation is paramount for securing placements in top companies. It ensures candidates can effectively demonstrate their technical skills and soft skills during the recruitment process.
Program Structure and Curriculum
Eligibility:
- Passed 10+2 examination with Physics and Mathematics as compulsory subjects along with one of the Chemistry/Biotechnology/Biology/Technical Vocational subject. Obtained at least 45% marks (40% for reserved category) in the above subjects taken together. Scores in JEE (Main), JEE (Advanced), Alliance University Engineering Entrance Test (AUEET), or any other State-level engineering entrance examination.
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 |
|---|---|---|---|---|
| U23ENG1010 | English for Communication | Program Core | 3 | Communication Skills, Grammar and Vocabulary, Reading Comprehension, Writing Skills, Presentation Techniques, Public Speaking |
| U23MAT1010 | Engineering Mathematics - I | Program Core | 4 | Differential Calculus, Integral Calculus, Multivariable Calculus, Vector Calculus, Differential Equations |
| U23PHE1010 | Engineering Physics | Program Core | 3 | Optics, Modern Physics, Quantum Mechanics, Solid State Physics, Lasers and Fiber Optics |
| U23PHEL1010 | Engineering Physics Lab | Program Core | 1 | Experimental Physics, Data Analysis, Error Analysis, Measurement Techniques, Lab Equipment Handling |
| U23CS1010 | Introduction to Problem Solving through Programming | Program Core | 3 | Programming Fundamentals, Algorithms, Data Types and Variables, Control Flow, Functions, Basic Input/Output |
| U23CSL1010 | Problem Solving through Programming Lab | Program Core | 1 | Hands-on Programming, Debugging Techniques, Problem Implementation, Code Testing, Practical Application |
| U23CE1010 | Elements of Civil Engineering | Program Core | 3 | Surveying, Building Materials, Structural Engineering, Transportation Engineering, Environmental Engineering, Water Resources |
| U23ME1010 | Elements of Mechanical Engineering | Program Core | 3 | Thermodynamics, Fluid Mechanics, Engineering Materials, Manufacturing Processes, Power Generation, Refrigeration |
| U23PD1010 | Professional Development Skills | Professional Development Course | 1 | Soft Skills, Teamwork, Leadership, Time Management, Career Planning |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| U23MAT2010 | Engineering Mathematics - II | Program Core | 4 | Linear Algebra, Laplace Transforms, Fourier Series, Probability Theory, Statistics, Numerical Methods |
| U23CHE2010 | Engineering Chemistry | Program Core | 3 | Electrochemistry, Corrosion, Water Technology, Fuels and Combustion, Polymers, Nanomaterials |
| U23CHEL2010 | Engineering Chemistry Lab | Program Core | 1 | Chemical Analysis, Volumetric Analysis, Instrumental Techniques, Synthesis Procedures, Material Characterization |
| U23EE2010 | Basic Electrical Engineering | Program Core | 3 | DC Circuits, AC Circuits, Transformers, Motors and Generators, Power Systems |
| U23EEL2010 | Basic Electrical Engineering Lab | Program Core | 1 | Circuit Laws, Electrical Measurements, Circuit Simulation, Wiring Practices, Component Testing |
| U23EC2010 | Basic Electronics Engineering | Program Core | 3 | Diodes and Rectifiers, Transistors, Amplifiers, Oscillators, Digital Electronics, Communication Systems |
| U23ECL2010 | Basic Electronics Engineering Lab | Program Core | 1 | Component Identification, Circuit Building, Oscilloscope Usage, Logic Gates, Breadboarding |
| U23MECH2010 | Engineering Graphics | Program Core | 3 | Orthographic Projections, Isometric Projections, Sectional Views, AutoCAD Introduction, Solid Modeling, Assembly Drawings |
| U23PD2010 | Professional Development Skills | Professional Development Course | 1 | Problem Solving, Critical Thinking, Creativity, Ethics, Entrepreneurship, Interview Skills |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| U23IT3010 | Data Structures & Algorithms | Program Core | 4 | Arrays and Linked Lists, Stacks and Queues, Trees and Graphs, Sorting Algorithms, Searching Algorithms, Hashing |
| U23ITL3010 | Data Structures & Algorithms Lab | Program Core | 1 | Implementation of Data Structures, Algorithm Analysis, Debugging Practices, Performance Testing, Problem Solving with DS |
| U23MAT3010 | Discrete Mathematical Structures | Program Core | 3 | Set Theory, Logic and Proof Techniques, Relations and Functions, Graph Theory, Combinatorics, Recurrence Relations |
| U23IT3020 | Digital Logic Design | Program Core | 3 | Boolean Algebra, Logic Gates, Combinational Circuits, Sequential Circuits, Registers and Counters, Memory Elements |
| U23ITL3020 | Digital Logic Design Lab | Program Core | 1 | Logic Gate ICs, Circuit Design and Simulation, Microcontroller Interfacing, Hardware Implementation, Troubleshooting Digital Circuits |
| U23IT3030 | Object Oriented Programming | Program Core | 3 | Classes and Objects, Inheritance, Polymorphism, Abstraction and Encapsulation, Exception Handling, File I/O |
| U23ITL3030 | Object Oriented Programming Lab | Program Core | 1 | OOP in Java/Python, Class Design, Application Development, Debugging OOP Programs, GUI Development Basics |
| U23IT3040 | Computer Organization and Architecture | Program Core | 4 | CPU Structure, Memory Hierarchy, I/O Organization, Instruction Sets, Pipelining, Addressing Modes |
| U23IT3050 | Universal Human Values | Program Core | 2 | Ethics and Morals, Human-Nature Relationship, Society and Family Values, Professional Ethics, Holistic Living |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| U23IT4010 | Database Management Systems | Program Core | 4 | Relational Model, SQL Queries, ER Diagrams, Normalization, Transactions and Concurrency, Indexing Techniques |
| U23ITL4010 | Database Management Systems Lab | Program Core | 1 | SQL Implementation, Database Design, Schema Implementation, PL/SQL Programming, NoSQL Basics |
| U23IT4020 | Operating Systems | Program Core | 4 | Process Management, Memory Management, File Systems, I/O Systems, Deadlocks, Scheduling Algorithms |
| U23ITL4020 | Operating Systems Lab | Program Core | 1 | Shell Scripting, System Calls, Process Synchronization, Memory Allocation Algorithms, OS Utilities |
| U23IT4030 | Design and Analysis of Algorithms | Program Core | 3 | Algorithm Complexity, Divide and Conquer, Greedy Algorithms, Dynamic Programming, Graph Algorithms, NP-Completeness |
| U23IT4040 | Probability and Statistics for IT | Program Core | 3 | Probability Distributions, Hypothesis Testing, Regression Analysis, Correlation, ANOVA, Sampling Techniques |
| U23IT4050 | Environmental Science & Sustainable Engineering | Program Core | 2 | Ecosystems and Biodiversity, Pollution Control, Renewable Energy, Waste Management, Climate Change Impacts, Sustainable Development |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| U23IT5010 | Theory of Computation | Program Core | 3 | Automata Theory, Regular Expressions, Context-Free Grammars, Turing Machines, Computability, Undecidability |
| U23IT5020 | Computer Networks | Program Core | 4 | OSI and TCP/IP Models, Network Topologies, Routing Protocols, Switching Technologies, Network Security Basics, Application Layer Protocols |
| U23ITL5020 | Computer Networks Lab | Program Core | 1 | Network Configuration, Socket Programming, Packet Analysis, Network Simulation Tools, Client-Server Communication |
| U23ITDA5110 | Advanced Database Management Systems | Specialization Elective - Data Analytics | 3 | Distributed Databases, Object-Oriented Databases, Data Warehousing Concepts, OLAP Operations, Data Mining Fundamentals, Big Data Storage |
| U23ITDA5120 | Data Visualization | Specialization Elective - Data Analytics | 3 | Visual Encoding, Chart Types, Interactive Dashboards, Data Storytelling, Visualization Tools (e.g., Tableau), Infographics Design |
| U23ITDA5130 | Foundations of Data Analytics | Specialization Elective - Data Analytics | 3 | Data Types and Sources, Data Preprocessing, Exploratory Data Analysis, Statistical Methods, Machine Learning Basics, Business Understanding |
| U23ITDA5140 | Big Data Fundamentals | Specialization Elective - Data Analytics | 3 | Hadoop Ecosystem, Distributed Storage (HDFS), MapReduce Framework, Spark Introduction, NoSQL Databases, Big Data Architectures |
| U23OE51xx | Open Elective - I | General Elective | 3 | Topics vary based on chosen elective |
| U23ITPW5010 | Semester Project - I | Project | 2 | Project Planning, Requirements Gathering, System Design, Implementation Basics, Testing and Documentation |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| U23IT6010 | Compiler Design | Program Core | 4 | Lexical Analysis, Syntax Analysis, Semantic Analysis, Intermediate Code Generation, Code Optimization, Runtime Environments |
| U23ITL6010 | Compiler Design Lab | Program Core | 1 | Lexer/Parser Tools (Lex/Yacc), Compiler Implementation, Code Generation, Debugging Compilers, Language Front-ends |
| U23IT6020 | Software Engineering | Program Core | 3 | SDLC Models, Requirements Engineering, Software Design Patterns, Testing and Quality Assurance, Project Management, Agile Methodologies |
| U23ITDA6110 | Machine Learning | Specialization Elective - Data Analytics | 3 | Supervised Learning, Unsupervised Learning, Regression Models, Classification Algorithms, Clustering Techniques, Model Evaluation |
| U23ITDA6120 | Data Warehousing and Data Mining | Specialization Elective - Data Analytics | 3 | ETL Process, Data Cubes and OLAP, Association Rule Mining, Classification Algorithms, Clustering Techniques, Predictive Analytics |
| U23ITDA6130 | Business Intelligence | Specialization Elective - Data Analytics | 3 | BI Architecture, Data Governance, Reporting Tools, Dashboards and KPIs, Decision Support Systems, Predictive Modeling |
| U23ITDA6140 | Natural Language Processing | Specialization Elective - Data Analytics | 3 | Text Preprocessing, Tokenization and POS Tagging, Named Entity Recognition, Sentiment Analysis, Text Classification, Language Models |
| U23OE61xx | Open Elective - II | General Elective | 3 | Topics vary based on chosen elective |
| U23ITPW6010 | Semester Project - II | Project | 2 | Advanced Project Management, System Development, Testing and Debugging, Report Writing, Technical Presentation |
Semester 7
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| U23IT7010 | Artificial Intelligence | Program Core | 3 | AI Agents, Search Algorithms, Knowledge Representation, Expert Systems, Machine Learning Foundations, Neural Networks Basics |
| U23ITL7010 | Artificial Intelligence Lab | Program Core | 1 | AI Programming (Python), Heuristic Search Implementation, Logic Programming, Machine Learning Libraries, AI Applications |
| U23ITDA7110 | Deep Learning | Specialization Elective - Data Analytics | 3 | Neural Networks, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Transfer Learning, TensorFlow/PyTorch, Deep Learning Architectures |
| U23ITDA7120 | Big Data Analytics | Specialization Elective - Data Analytics | 3 | Hadoop Ecosystem (Advanced), Spark Programming, Hive and Pig, Scala for Big Data, Real-time Analytics, Stream Processing |
| U23ITDA7130 | Reinforcement Learning | Specialization Elective - Data Analytics | 3 | Markov Decision Processes, Q-Learning, Policy Gradients, Deep Reinforcement Learning, Exploration-Exploitation, RL Applications |
| U23ITDA7140 | Social Network Analysis | Specialization Elective - Data Analytics | 3 | Network Metrics, Community Detection, Link Prediction, Influence Maximization, Graph Databases, Network Visualization |
| U23OE71xx | Open Elective - III | General Elective | 3 | Topics vary based on chosen elective |
| U23ITIPW7010 | Industrial Internship / Project Work | Internship/Project | 10 | Industry Exposure, Real-world Problem Solving, Project Implementation, Professional Communication, Technical Report Writing, Presentation Skills |
Semester 8
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| U23ITDA8110 | Data Ethics and Governance | Specialization Elective - Data Analytics | 3 | Data Privacy and Security, Bias and Fairness in AI, Ethical AI Principles, Data Regulations (GDPR, DPA), Data Lifecycle Management, Compliance and Auditing |
| U23ITDA8120 | Time Series Analysis | Specialization Elective - Data Analytics | 3 | ARIMA Models, Exponential Smoothing, Stationarity and Seasonality, Forecasting Techniques, Spectral Analysis, Financial Data Analysis |
| U23ITDA8130 | Cloud Data Platforms | Specialization Elective - Data Analytics | 3 | AWS Data Services, Azure Data Services, GCP Data Services, Serverless Computing, Data Lakes and Warehouses in Cloud, Cloud Security for Data |
| U23ITDA8140 | Research Methodology | Specialization Elective - Data Analytics | 3 | Research Design, Data Collection Methods, Statistical Analysis, Thesis Writing, Plagiarism and Ethics, Report Formulation |
| U23ITPRJ8010 | Project Work | Major Project | 10 | Comprehensive Project Development, Research and Literature Review, Advanced System Design, Implementation and Testing, Technical Documentation, Public Presentation and Defense |
| U23ITSEM8010 | Technical Seminar | Seminar | 1 | Technical Presentation, Literature Review, Public Speaking Skills, Emerging Technologies, Peer Feedback, Research Communication |
