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B-TECH-BACHELOR-OF-TECHNOLOGY-SIT-PUNE in Artificial Intelligence And Machine Learning at Symbiosis International University (SIU)
Pune, Maharashtra
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About the Specialization
What is Artificial Intelligence and Machine Learning at Symbiosis International University (SIU) Pune?
This Artificial Intelligence and Machine Learning program at Symbiosis Institute of Technology focuses on equipping students with expertise in intelligent systems, data analysis, and predictive modeling. India''''s rapidly growing tech sector, especially in areas like FinTech, healthcare, and e-commerce, demands skilled AI/ML professionals. The program emphasizes a blend of theoretical foundations and practical applications, preparing graduates for cutting-edge roles.
Who Should Apply?
This program is ideal for analytically minded fresh graduates with a strong foundation in mathematics and programming seeking entry into high-growth technology fields. It also benefits working professionals looking to pivot into AI/ML roles or upskill to meet industry demands. Candidates interested in research, innovation, and developing smart solutions for real-world problems will find this specialization particularly rewarding.
Why Choose This Course?
Graduates of this program can expect diverse career paths in India, including AI Engineer, Machine Learning Scientist, Data Scientist, NLP Engineer, and Computer Vision Specialist. Entry-level salaries typically range from INR 6-12 LPA, with experienced professionals earning significantly more. The curriculum aligns with requirements for professional certifications and offers growth trajectories into leadership roles in Indian tech companies and startups.
Student Success Practices
Foundation Stage
Master Programming Fundamentals- (Semester 1-2)
Dedicate significant time to mastering programming logic and data structures in C/Python. Actively participate in coding platforms to solve problems consistently.
Tools & Resources
HackerRank, LeetCode, GeeksforGeeks, CodeChef, NPTEL courses on Data Structures
Career Connection
Strong coding skills are fundamental for all tech roles and essential for clearing technical rounds in placements.
Build a Strong Mathematical Core- (Semester 1-2)
Focus on understanding concepts in Engineering Mathematics, Probability, and Statistics thoroughly. These form the bedrock for advanced AI/ML algorithms.
Tools & Resources
Khan Academy, MIT OpenCourseware, textbooks, peer study groups, practicing problems from diverse sources
Career Connection
A solid mathematical foundation is crucial for grasping complex ML algorithms and contributing to research or advanced development roles.
Engage in Project-Based Learning- (Semester 1-2)
Actively contribute to and seek out opportunities for Project-Based Learning modules. Even small projects build practical skills and help apply theoretical knowledge.
Tools & Resources
GitHub for version control, collaborative coding tools, online tutorials for beginner projects
Career Connection
Early project experience demonstrates initiative and provides talking points during internships and job interviews.
Intermediate Stage
Develop Specialization-Specific Skills- (Semester 3-5)
Dive deep into core AI/ML subjects like Data Science, Introduction to AI, Machine Learning, and Deep Learning. Start building a portfolio of specialized projects.
Tools & Resources
Kaggle for datasets and competitions, TensorFlow, PyTorch, Scikit-learn, Google Colab
Career Connection
This stage builds the technical expertise directly relevant to AI/ML job descriptions and advanced research opportunities.
Seek Early Industry Exposure- (Semester 3-5)
Look for relevant internships during summer breaks, even if unpaid initially. Network with professionals through LinkedIn and industry events.
Tools & Resources
LinkedIn, Internshala, company career pages, campus career fairs, industry webinars
Career Connection
Internships provide invaluable real-world experience, help understand industry expectations, and can often lead to pre-placement offers.
Participate in Hackathons and Competitions- (Semester 3-5)
Engage in AI/ML hackathons and coding competitions to test skills, learn from peers, and build innovative solutions under time pressure.
Tools & Resources
DevPost, Major League Hacking (MLH), Kaggle competitions, local college tech festivals
Career Connection
Showcases problem-solving abilities, teamwork, and innovation, making resumes stand out to recruiters in India''''s competitive tech landscape.
Advanced Stage
Undertake Significant Projects and Research- (Semester 6-8)
Focus on major and minor projects that solve complex, real-world problems, ideally with an industry mentor or faculty advisor. Consider research paper publications.
Tools & Resources
Advanced ML/DL frameworks, cloud platforms (AWS, Azure, GCP), academic research databases
Career Connection
High-impact projects demonstrate advanced capabilities and are critical for securing top placements or pursuing higher studies/research.
Intensive Placement Preparation- (Semester 6-8)
Practice technical interviews, aptitude tests, and soft skills required for placements. Tailor your resume and portfolio to specific job roles in AI/ML.
Tools & Resources
InterviewBit, LeetCode, Glassdoor, mock interview sessions, career counseling services at SIT Pune
Career Connection
Comprehensive preparation is vital for converting skills into desirable job offers at leading Indian and international companies.
Network and Professional Development- (Semester 6-8)
Expand your professional network by attending conferences, workshops, and alumni events. Explore advanced certifications in specialized AI/ML domains.
Tools & Resources
Industry conferences (e.g., Data Science Congress, AI Summit), professional organizations (e.g., IEEE, ACM), Coursera, edX for specialized courses
Career Connection
Networking opens doors to mentorship, collaborative opportunities, and insights into emerging industry trends, facilitating long-term career growth in India.
Program Structure and Curriculum
Eligibility:
- Passed 10+2 with Physics and Mathematics as compulsory subjects along with one of Chemistry/Biotechnology/Biology/Technical Vocational subjects. Obtained at least 45% marks (40% for SC/ST) in the above subjects taken together. Valid score in SITEEE/JEE (Main)/MHT-CET.
Duration: 4 years (8 semesters)
Credits: 160 Credits
Assessment: Internal: 50%, External: 50%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 070112101 | Engineering Mathematics-I | Core | 4 | Differential Calculus, Integral Calculus, Ordinary Differential Equations, Multivariable Calculus, Vector Calculus |
| 070112102 | Engineering Physics | Core | 4 | Optics, Quantum Mechanics, Solid State Physics, Lasers and Fiber Optics, Nanotechnology |
| 070112103 | Basic Electrical Engineering | Core | 4 | DC Circuits, AC Circuits, Transformers, Electrical Machines, Semiconductor Devices |
| 070112104 | Programming for Problem Solving | Core | 4 | Introduction to C Programming, Control Statements, Functions, Arrays, Pointers, Structures |
| 070112105 | Engineering Graphics | Core | 2 | Engineering Drawing Instruments, Orthographic Projections, Isometric Projections, Sectional Views, AutoCAD Basics |
| 070112106 | Engineering Physics Lab | Lab | 1 | Experiments related to Optics, Lasers, Semiconductor Devices, Magnetic Fields, Sound |
| 070112107 | Basic Electrical Engineering Lab | Lab | 1 | Experiments on DC and AC circuits, Verification of network theorems, Transformer characteristics, Diode and Transistor characteristics |
| 070112108 | Programming for Problem Solving Lab | Lab | 1 | C programming exercises, Data type operations, Control flow applications, Function implementation, Array and string manipulation |
| 070112109 | Project Based Learning-I | Project | 2 | Problem identification, Literature survey, Design thinking, Prototyping, Report writing |
| 070112110 | Universal Human Values-I | Core | 2 | Self-exploration, Human aspirations, Harmony in family, Harmony in society, Universal Human Order |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 070112201 | Engineering Mathematics-II | Core | 4 | Matrices, Linear Algebra, Multiple Integrals, Vector Spaces, Eigenvalues and Eigenvectors |
| 070112202 | Engineering Chemistry | Core | 4 | Water Technology, Fuels and Combustion, Corrosion and its Control, Engineering Materials, Polymer Chemistry |
| 070112203 | Digital Electronics | Core | 4 | Number Systems, Logic Gates, Boolean Algebra, Combinational Circuits, Sequential Circuits |
| 070112204 | Data Structures | Core | 4 | Arrays, Linked Lists, Stacks, Queues, Trees, Graphs |
| 070112205 | Engineering Mechanics | Core | 2 | Force Systems, Equilibrium, Friction, Centroid and Moment of Inertia, Kinematics and Kinetics |
| 070112206 | Engineering Chemistry Lab | Lab | 1 | Volumetric analysis, Instrumental analysis, Water hardness determination, Fuel analysis, Viscosity experiments |
| 070112207 | Digital Electronics Lab | Lab | 1 | Implementation of logic gates, Design of adders/subtractors, Flip-flops, Counters, Shift registers |
| 070112208 | Data Structures Lab | Lab | 1 | Implementation of arrays, Linked lists, Stacks, Queues, Tree traversals, Graph algorithms |
| 070112209 | Project Based Learning-II | Project | 2 | Project planning, Team collaboration, Prototype development, Testing, Presentation skills |
| 070112210 | Universal Human Values-II | Core | 2 | Relationship, Trust, Respect, Justice, Co-existence |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 070112301 | Discrete Mathematics | Core | 4 | Set Theory, Logic and Proofs, Relations and Functions, Graph Theory, Recurrence Relations |
| 070112302 | Computer Organization and Architecture | Core | 4 | Basic Computer Organization, CPU Design, Memory Hierarchy, I/O Organization, Pipelining |
| 070112303 | Object Oriented Programming | Core | 4 | Classes and Objects, Inheritance, Polymorphism, Abstraction, Encapsulation, Exception Handling |
| 070112304 | Database Management Systems | Core | 4 | Database Architecture, ER Model, Relational Model, SQL, Normalization, Transaction Management |
| 070112305 | Fundamentals of Data Science | Core | 3 | Introduction to Data Science, Data Preprocessing, Exploratory Data Analysis, Statistical Inference, Data Visualization |
| 070112306 | Computer Organization and Architecture Lab | Lab | 1 | Assembly language programming, CPU simulation, Memory organization experiments, I/O interfacing |
| 070112307 | Object Oriented Programming Lab | Lab | 1 | C++ or Java programming, Class and object implementation, Inheritance hierarchy, Polymorphism applications |
| 070112308 | Database Management Systems Lab | Lab | 1 | SQL queries, Database design, Schema creation, Data manipulation, Transaction implementation |
| 070112309 | Mini Project-I | Project | 2 | Project proposal, System design, Implementation, Testing and debugging, Documentation |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 070112401 | Probability and Statistics | Core | 4 | Probability Theory, Random Variables, Probability Distributions, Hypothesis Testing, Regression and Correlation |
| 070112402 | Operating Systems | Core | 4 | Process Management, CPU Scheduling, Memory Management, File Systems, I/O Systems |
| 070112403 | Design and Analysis of Algorithms | Core | 4 | Algorithm Analysis, Sorting and Searching, Greedy Algorithms, Dynamic Programming, Graph Algorithms |
| 070112404 | Introduction to Artificial Intelligence | Core | 3 | AI History, Problem Solving Agents, Search Algorithms, Game Playing, Knowledge Representation, Machine Learning Basics |
| 070112405 | Programming in Python | Core | 3 | Python Fundamentals, Data Structures in Python, Functions, Object-Oriented Programming, File I/O, Libraries for Data Science |
| 070112406 | Operating Systems Lab | Lab | 1 | Linux commands, Shell scripting, Process synchronization, Deadlock prevention, Memory allocation algorithms |
| 070112407 | Design and Analysis of Algorithms Lab | Lab | 1 | Implementation of sorting, Searching, Graph, Dynamic programming algorithms |
| 070112408 | Artificial Intelligence Lab | Lab | 1 | Implementation of search algorithms, Logic programming, AI problem-solving, Basic AI agent development |
| 070112409 | Mini Project-II | Project | 2 | Advanced project design, Module integration, Testing strategies, Performance evaluation, Technical report |
| 070112410 | Environmental Studies | Core | 2 | Natural Resources, Ecosystems, Biodiversity Conservation, Environmental Pollution, Social Issues and the Environment |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 070112501 | Compiler Design | Core | 4 | Lexical Analysis, Syntax Analysis, Semantic Analysis, Intermediate Code Generation, Code Optimization |
| 070112502 | Computer Networks | Core | 4 | OSI Model, TCP/IP Protocol Suite, Network Layer, Transport Layer, Application Layer, Network Security |
| 070112503 | Machine Learning | Core | 4 | Supervised Learning, Unsupervised Learning, Reinforcement Learning, Model Evaluation, Ensemble Methods, Neural Networks |
| 070112504 | Deep Learning | Core | 3 | Neural Network Architectures, Convolutional Neural Networks, Recurrent Neural Networks, Transformers, Generative Models |
| 070112505 | Compiler Design Lab | Lab | 1 | Lexical analyzer implementation, Parser development, Syntax tree generation, Intermediate code generation |
| 070112506 | Computer Networks Lab | Lab | 1 | Network configuration, Socket programming, Protocol implementation, Network traffic analysis |
| 070112507 | Machine Learning Lab | Lab | 1 | Implementation of ML algorithms, Data preprocessing, Model training and evaluation, Scikit-learn, TensorFlow/PyTorch |
| 070112508 | Deep Learning Lab | Lab | 1 | CNN and RNN implementation, Transfer learning, Image recognition, Natural language processing tasks |
| 070112509A | Elective-I (Theory of Computation) | Elective | 3 | Finite Automata, Regular Expressions, Context-Free Grammars, Turing Machines, Undecidability |
| 070112509B | Elective-I (Data Warehousing and Mining) | Elective | 3 | Data Warehouse Architecture, ETL Process, OLAP, Data Mining Techniques, Association Rules, Classification, Clustering |
| 070112509C | Elective-I (Software Engineering) | Elective | 3 | Software Development Life Cycle, Requirements Engineering, Software Design, Testing, Project Management |
| 070112510 | Open Elective-I | Elective | 3 | Choice of interdisciplinary subjects |
| 070112511 | Internship-I / Value-Added Course | Internship/Value-Added | 1 | Industry exposure, Practical skills, Professional development, Project work |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 070112601 | Natural Language Processing | Core | 4 | Text Preprocessing, Language Models, Part-of-Speech Tagging, Sentiment Analysis, Machine Translation, Text Generation |
| 070112602 | Computer Vision | Core | 4 | Image Formation, Image Preprocessing, Feature Extraction, Object Detection, Image Segmentation, Facial Recognition |
| 070112603 | Reinforcement Learning | Core | 3 | Markov Decision Processes, Value Iteration, Policy Iteration, Q-Learning, SARSA, Deep Reinforcement Learning |
| 070112604 | Natural Language Processing Lab | Lab | 1 | Text corpus processing, NLTK library usage, POS tagging, Named entity recognition, Chatbot development |
| 070112605 | Computer Vision Lab | Lab | 1 | OpenCV library, Image filtering, Edge detection, Object tracking, Image classification |
| 070112606 | Reinforcement Learning Lab | Lab | 1 | Implementation of RL algorithms, OpenAI Gym, Q-Learning agent, Policy gradient methods |
| 070112607A | Elective-II (Cloud Computing) | Elective | 3 | Cloud Architecture, Service Models (IaaS, PaaS, SaaS), Deployment Models, Virtualization, Cloud Security |
| 070112607B | Elective-II (Big Data Analytics) | Elective | 3 | Big Data Technologies, Hadoop Ecosystem, Spark, NoSQL Databases, Data Streaming, Big Data Applications |
| 070112607C | Elective-II (Image Processing) | Elective | 3 | Digital Image Fundamentals, Image Enhancement, Image Restoration, Image Compression, Morphological Image Processing |
| 070112608A | Elective-III (Web Technologies) | Elective | 3 | HTML5, CSS3, JavaScript, Web Frameworks, Server-Side Scripting, Web Security |
| 070112608B | Elective-III (Information Retrieval) | Elective | 3 | Boolean Retrieval, Vector Space Model, Text Classification, Clustering, Web Search Engines, Link Analysis |
| 070112608C | Elective-III (Distributed Systems) | Elective | 3 | Distributed System Architecture, Client-Server Model, RPC, Distributed File Systems, Consensus Algorithms, Distributed Transactions |
| 070112609 | Open Elective-II | Elective | 3 | Choice of interdisciplinary subjects |
| 070112610 | Mini Project-III | Project | 2 | Problem formulation, System architecture, Implementation challenges, Data analysis, Project demonstration |
Semester 7
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 070112701 | AI Ethics and Governance | Core | 3 | Ethical AI Principles, Bias in AI, AI Fairness, Data Privacy, Legal Implications, Responsible AI Development |
| 070112702 | Minor Project | Project | 6 | Problem formulation, Design and implementation, Experimental validation, Result analysis, Technical report writing |
| 070112703A | Elective-IV (Robotics Process Automation) | Elective | 3 | RPA Fundamentals, RPA Tools, Process Mapping, Automation Bots, RPA Implementation, Benefits of RPA |
| 070112703B | Elective-IV (Blockchain Technologies) | Elective | 3 | Cryptography, Distributed Ledger, Blockchain Architecture, Smart Contracts, Cryptocurrency, Blockchain Applications |
| 070112703C | Elective-IV (Human Computer Interaction) | Elective | 3 | HCI Principles, Usability Engineering, User Centered Design, Prototyping, Evaluation Methods, Interface Design |
| 070112704A | Elective-V (Game Theory) | Elective | 3 | Strategic Games, Nash Equilibrium, Extensive Form Games, Cooperative Games, Mechanism Design, Evolutionary Game Theory |
| 070112704B | Elective-V (Fuzzy Logic and Neural Networks) | Elective | 3 | Fuzzy Sets, Fuzzy Relations, Fuzzy Systems, Artificial Neural Networks, Backpropagation, Genetic Algorithms |
| 070112704C | Elective-V (Internet of Things) | Elective | 3 | IoT Architecture, Sensors and Actuators, IoT Protocols, Cloud Integration, IoT Security, Smart Applications |
| 070112705 | Open Elective-III | Elective | 3 | Choice of interdisciplinary subjects |
| 070112706 | Internship-II / Value-Added Course | Internship/Value-Added | 1 | Advanced industry projects, Professional networking, Skill enhancement, Career preparation |
Semester 8
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 070112801 | Major Project | Project | 12 | Comprehensive system development, Research methodology, Innovation, Industrial standards, Project defense |
| 070112802A | Elective-VI (Computer Graphics) | Elective | 3 | Graphics Hardware, 2D and 3D Transformations, Viewing, Shading, Texture Mapping, Animation |
| 070112802B | Elective-VI (Quantum Computing) | Elective | 3 | Quantum Mechanics Basics, Qubits, Quantum Gates, Quantum Algorithms, Quantum Cryptography |
| 070112802C | Elective-VI (Research Methodology) | Elective | 3 | Research Problem Identification, Literature Review, Research Design, Data Collection, Statistical Analysis, Thesis Writing |
| 070112803A | Elective-VII (Business Intelligence) | Elective | 3 | BI Architecture, Data Integration, Data Visualization, Reporting, Dashboards, Predictive Analytics |
| 070112803B | Elective-VII (Cyber Security) | Elective | 3 | Network Security, Cryptography, Web Security, Malware, Cyber Forensics, Security Policies |
| 070112803C | Elective-VII (Augmented and Virtual Reality) | Elective | 3 | AR/VR Devices, 3D Graphics, Interaction Techniques, Tracking, Immersion, AR/VR Applications |
