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B-TECH in Artificial Intelligence And Data Science at Datta Meghe Institute of Medical Sciences (Deemed to be University)
Wardha, Maharashtra
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About the Specialization
What is Artificial Intelligence and Data Science at Datta Meghe Institute of Medical Sciences (Deemed to be University) Wardha?
This Artificial Intelligence and Data Science program at Datta Meghe Institute of Higher Education and Research focuses on equipping students with expertise in machine learning, deep learning, big data analytics, and intelligent systems. It addresses the rapidly growing demand for skilled professionals in India''''s digital transformation journey, preparing graduates for cutting-edge roles in data-driven industries.
Who Should Apply?
This program is ideal for fresh 10+2 graduates with a strong aptitude for mathematics and problem-solving, seeking entry into the booming AI/DS field. It also benefits working professionals looking to upskill in advanced analytics, and career changers transitioning into data science or machine learning engineering roles across various sectors in India.
Why Choose This Course?
Graduates of this program can expect to pursue India-specific career paths such as Data Scientist, Machine Learning Engineer, AI Developer, and Big Data Analyst. Entry-level salaries typically range from INR 4-8 LPA, with experienced professionals earning upwards of INR 15-25 LPA in leading Indian companies and startups. The curriculum aligns with industry certifications, fostering continuous growth.
Student Success Practices
Foundation Stage
Master Programming Fundamentals- (Semester 1-2)
Focus rigorously on C and Python programming, understanding core concepts like data structures and algorithms. Participate in coding competitions to hone problem-solving skills beyond classroom exercises.
Tools & Resources
HackerRank, LeetCode, GeeksforGeeks, Python documentation
Career Connection
Strong programming skills are the bedrock for any AI/DS role, crucial for cracking technical interviews and developing efficient algorithms.
Build Strong Mathematical & Statistical Foundations- (Semester 1-2)
Dedicate time to understanding engineering mathematics, particularly linear algebra, calculus, probability, and statistics. These are critical for grasping the theoretical underpinnings of AI and Data Science algorithms.
Tools & Resources
Khan Academy, NPTEL courses, reference textbooks by Grewal, Spiegel
Career Connection
A robust mathematical base enables deeper understanding of model behavior, algorithm selection, and independent research in advanced AI/DS topics.
Cultivate Professional Communication- (Semester 1-2)
Actively participate in communication skills labs and group projects to improve both written and verbal communication. Practice presenting technical concepts clearly and concisely to diverse audiences.
Tools & Resources
Toastmasters International, LinkedIn Learning courses on presentation skills
Career Connection
Effective communication is vital for collaborating in teams, presenting project outcomes to stakeholders, and excelling in interviews for roles in Indian companies.
Intermediate Stage
Hands-On Data Science & ML Projects- (Semester 3-5)
Beyond lab assignments, proactively seek out and complete mini-projects using real-world datasets. Focus on applying concepts from Data Structures, DBMS, and Machine Learning to solve practical problems.
Tools & Resources
Kaggle, GitHub, Google Colab, scikit-learn, Pandas, NumPy
Career Connection
A strong project portfolio demonstrates practical skills to Indian recruiters, making candidates stand out for internships and entry-level Data Scientist/ML Engineer roles.
Network and Seek Industry Exposure- (Semester 3-5)
Attend webinars, workshops, and industry meetups related to AI and Data Science. Connect with professionals on platforms like LinkedIn and explore potential mentors or internship opportunities in Indian tech hubs.
Tools & Resources
LinkedIn, industry conferences (e.g., India AI Summit), local tech communities
Career Connection
Networking opens doors to internships, provides insights into industry trends, and can lead to direct placement opportunities with top Indian companies.
Specialize with Electives and Advanced Concepts- (Semester 4-5)
Choose professional electives like Deep Learning strategically, aligning them with your career interests. Delve deeper into these areas through online courses and advanced textbooks to build specialized expertise.
Tools & Resources
Coursera, edX, fast.ai, TensorFlow/PyTorch official documentation
Career Connection
Specialization in high-demand areas like Deep Learning or NLP significantly increases employability and potential salary packages in the competitive Indian AI job market.
Advanced Stage
Undertake a Capstone Major Project- (Semester 7-8)
Invest significant effort into your major project, aiming for an innovative solution to a real-world problem in AI/DS. Focus on robust implementation, detailed documentation, and impactful presentation.
Tools & Resources
Advanced AI/ML libraries, cloud platforms (AWS, Azure), project management tools
Career Connection
A well-executed major project serves as a powerful resume builder, showcasing problem-solving abilities and readiness for R&D or advanced development roles.
Prepare for Placements and Interviews- (Semester 6-8)
Systematically practice aptitude tests, technical coding rounds, and HR interviews. Focus on data structures, algorithms, ML concepts, and scenario-based questions relevant to AI/DS roles in Indian companies.
Tools & Resources
InterviewBit, LeetCode, company-specific interview prep guides, mock interviews
Career Connection
Thorough preparation is key to securing coveted placements with leading Indian IT services, product companies, and startups offering AI/DS roles.
Engage in Internships and Real-World Experience- (Semester 6-8)
Actively pursue and complete internships in relevant AI/DS domains. Gain practical experience with industry workflows, team collaboration, and applying academic knowledge to solve business challenges.
Tools & Resources
College placement cell, Internshala, LinkedIn, company career pages
Career Connection
Internships provide invaluable practical exposure, often leading to pre-placement offers, and make candidates highly attractive to employers seeking job-ready talent in India.
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% in case of candidates belonging to reserved category) in the above subjects taken together.
Duration: 8 semesters/ 4 years
Credits: 168 Credits
Assessment: Internal: 40%, External: 60%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BTES101T | Engineering Mathematics-I | Core | 4 | Differential Calculus, Integral Calculus, Ordinary Differential Equations, Partial Differential Equations, Multiple Integrals |
| BTES102T | Engineering Physics | Core | 4 | Waves and Oscillations, Quantum Mechanics, Solid State Physics, Optics, Nuclear Physics |
| BTES103T | Engineering Chemistry | Core | 4 | Chemical Bonding, Electrochemistry, Organic Chemistry, Environmental Chemistry, Polymer Chemistry |
| BTES104T | Basic Electrical Engineering | Core | 4 | DC Circuits, AC Circuits, Electrical Machines, Transformers, Power Systems |
| BTES105P | Engineering Physics Lab | Lab | 1 | Waves Experiments, Optics Experiments, Electronics Experiments, Magnetism Experiments, Modern Physics Applications |
| BTES106P | Engineering Chemistry Lab | Lab | 1 | Volumetric Analysis, Chemical Kinetics, Organic Synthesis, Water Analysis, Spectroscopy |
| BTES107P | Basic Electrical Engineering Lab | Lab | 1 | Ohm''''s Law Verification, Kirchhoff''''s Laws, AC/DC Circuit Analysis, Motor Characteristics, Generator Principles |
| BTHM108T | Communication Skills | Core | 2 | Listening Skills, Speaking Skills, Reading Comprehension, Writing Skills, Presentation Techniques |
| BTHM109P | Communication Skills Lab | Lab | 1 | Group Discussions, Public Speaking Practice, Interview Skills, Presentations, Role Plays |
| BTPW110P | Workshop Practice | Lab | 1 | Fitting Operations, Carpentry Joints, Welding Techniques, Sheet Metal Work, Basic Machining |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BTES201T | Engineering Mathematics-II | Core | 4 | Linear Algebra, Vector Calculus, Laplace Transforms, Fourier Series, Complex Analysis |
| BTES202T | Computer Programming | Core | 4 | C Programming Basics, Control Structures, Functions, Arrays and Pointers, Structures and File I/O |
| BTES203T | Engineering Graphics & Design | Core | 3 | Orthographic Projections, Isometric Projections, Sectional Views, CAD Software Basics, Assembly Drawings |
| BTES204T | Environmental Science | Core | 2 | Ecosystems, Environmental Pollution, Natural Resources, Biodiversity Conservation, Environmental Laws |
| BTES205P | Computer Programming Lab | Lab | 1 | C Programming Exercises, Problem Solving, Debugging Techniques, Basic Algorithm Implementation, Code Optimization |
| BTES206P | Engineering Graphics & Design Lab | Lab | 1 | 2D Drawing using CAD, 3D Modeling Basics, Assembly Creation, Part Drawing, Drafting Standards |
| BTES207T | Professional Ethics | Core | 2 | Ethical Theories, Professionalism, Intellectual Property, Cybersecurity Ethics, Corporate Social Responsibility |
| BTCS208T | Data Structures | Core | 4 | Arrays and Linked Lists, Stacks and Queues, Trees and Graphs, Sorting Algorithms, Searching Techniques |
| BTCS209P | Data Structures Lab | Lab | 1 | Implementation of Linked Lists, Stack and Queue Operations, Tree Traversal Algorithms, Graph Algorithms Implementation, Sorting and Searching Programs |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BTES301T | Engineering Mathematics-III | Core | 4 | Probability Theory, Random Variables, Probability Distributions, Statistical Inference, Regression Analysis |
| BTCS302T | Object-Oriented Programming | Core | 4 | OOP Concepts, Classes and Objects, Inheritance and Polymorphism, Exception Handling, File I/O in Java |
| BTCS303T | Database Management Systems | Core | 4 | Data Models, ER Diagrams, Relational Algebra, SQL Queries, Normalization and Transactions |
| BTCS304T | Discrete Mathematics | Core | 4 | Set Theory and Logic, Relations and Functions, Graph Theory, Combinatorics, Algebraic Structures |
| BTCS305P | Object-Oriented Programming Lab | Lab | 1 | Java Programming, Class and Object Implementation, Inheritance Examples, Polymorphism Applications, Exception Handling Practice |
| BTCS306P | Database Management Systems Lab | Lab | 1 | SQL DDL and DML Commands, Database Design, Join Operations, Stored Procedures, Transaction Control |
| BTES307T | Constitution of India | Core | 2 | Preamble and Fundamental Rights, Directive Principles of State Policy, Union and State Government, Judiciary in India, Constitutional Amendments |
| BTPW308P | Mini Project-I | Project | 3 | Problem Identification, System Design, Implementation Phase, Testing and Debugging, Project Report Writing |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BTCS401T | Operating Systems | Core | 4 | Process Management, CPU Scheduling, Memory Management, File Systems, Deadlocks |
| BTCS402T | Design & Analysis of Algorithms | Core | 4 | Algorithm Analysis, Divide and Conquer, Dynamic Programming, Greedy Algorithms, Graph Algorithms |
| BTCS403T | Theory of Computation | Core | 4 | Finite Automata, Regular Expressions, Context-Free Grammars, Pushdown Automata, Turing Machines |
| BTCS404T | Data Science Fundamentals | Core | 4 | Introduction to Data Science, Data Collection and Preprocessing, Exploratory Data Analysis, Data Visualization Techniques, Basic Machine Learning |
| BTCS405P | Operating Systems Lab | Lab | 1 | Shell Scripting, Process Management, Memory Allocation Algorithms, System Calls, File Operations |
| BTCS406P | Design & Analysis of Algorithms Lab | Lab | 1 | Implementation of Sorting Algorithms, Graph Algorithm Practical, Dynamic Programming Solutions, Greedy Algorithm Problems, Complexity Analysis |
| BTCS407P | Data Science Fundamentals Lab | Lab | 1 | Data Loading and Cleaning, Data Visualization using Python, Basic Statistical Analysis, Simple Machine Learning Models, Data Preprocessing Techniques |
| BTPE408T | Python Programming (Professional Elective - I) | Elective | 3 | Python Basics, Data Structures in Python, Functions and Modules, Object-Oriented Python, NumPy and Pandas |
| BTCS409P | Python Programming Lab | Lab | 1 | Python Scripting, Data Manipulation, Web Scraping Basics, API Interaction, GUI Development |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BTCS501T | Artificial Intelligence | Core | 4 | Introduction to AI, Problem Solving with Search, Knowledge Representation, Logic Programming, Expert Systems |
| BTCS502T | Machine Learning | Core | 4 | Supervised Learning, Unsupervised Learning, Reinforcement Learning Basics, Model Evaluation Metrics, Feature Engineering |
| BTCS503T | Computer Networks | Core | 4 | Network Models (OSI, TCP/IP), Data Link Layer, Network Layer (IP, Routing), Transport Layer (TCP, UDP), Application Layer Protocols |
| BTCS504P | Artificial Intelligence Lab | Lab | 1 | Prolog Programming, Search Algorithm Implementation, AI Game Playing, Logic Programming Exercises, Expert System Shells |
| BTCS505P | Machine Learning Lab | Lab | 1 | Regression Model Implementation, Classification Model Development, Clustering Techniques, Scikit-learn usage, TensorFlow/PyTorch Basics |
| BTCS506P | Computer Networks Lab | Lab | 1 | Network Configuration, Socket Programming, Protocol Analysis, Network Simulation Tools, Client-Server Applications |
| BTPE507T | Deep Learning (Professional Elective - II) | Elective | 3 | Neural Networks, Backpropagation, Convolutional Neural Networks, Recurrent Neural Networks, Deep Learning Frameworks |
| BTPE508P | Deep Learning Lab | Lab | 1 | CNN Implementation, RNN Model Development, Image Classification, Sequence Prediction, Transfer Learning |
| BTHM509T | Entrepreneurship Development | Core | 2 | Entrepreneurial Mindset, Business Plan Development, Marketing Strategies, Financial Management, Innovation and Creativity |
| BTPW510P | Mini Project-II | Project | 2 | Project Design, Development Lifecycle, Testing and Validation, Presentation Skills, Technical Report Writing |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BTCS601T | Big Data Analytics | Core | 4 | Big Data Ecosystem, Hadoop and Spark, MapReduce Framework, NoSQL Databases, Stream Processing |
| BTCS602T | Natural Language Processing | Core | 4 | NLP Fundamentals, Text Preprocessing, Tokenization and POS Tagging, Named Entity Recognition, Sentiment Analysis |
| BTCS603T | Cloud Computing | Core | 4 | Cloud Paradigms (IaaS, PaaS, SaaS), Virtualization Technology, Cloud Security Aspects, Cloud Deployment Models, Cloud Services (AWS, Azure, GCP) |
| BTCS604P | Big Data Analytics Lab | Lab | 1 | Hadoop Ecosystem Setup, MapReduce Programming, Spark Data Processing, HDFS Operations, NoSQL Database Interaction |
| BTCS605P | Natural Language Processing Lab | Lab | 1 | NLTK Library Usage, Text Classification, Word Embeddings, Language Modeling, Seq2Seq Models |
| BTCS606P | Cloud Computing Lab | Lab | 1 | Virtual Machine Deployment, Cloud Storage Services, Serverless Computing, Containerization (Docker), Cloud Security Configuration |
| BTPE607T | Reinforcement Learning (Professional Elective - III) | Elective | 3 | Markov Decision Processes, Value and Policy Iteration, Q-Learning Algorithm, SARSA Algorithm, Deep Reinforcement Learning |
| BTPE608P | Reinforcement Learning Lab | Lab | 1 | RL Environment Setup, Q-Learning Implementation, Policy Gradient Methods, Deep Q-Networks, Agent Training |
| BTPW609P | Mini Project-III | Project | 3 | Advanced AI/DS Project, Research Methodology, System Development, Performance Evaluation, Technical Documentation |
Semester 7
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BTCS701T | Data Visualization Techniques | Core | 4 | Principles of Visualization, Visual Perception, Data Storytelling, Interactive Visualizations, Visualization Tools (Tableau, Power BI) |
| BTCS702T | Ethical Hacking & Cyber Security | Core | 4 | Network Security, Cryptography, Web Application Security, Malware Analysis, Ethical Hacking Methodologies |
| BTCS703P | Data Visualization Techniques Lab | Lab | 1 | Matplotlib and Seaborn, Plotly and Bokeh, Dashboard Creation, Interactive Charts, Data Storytelling Practices |
| BTCS704P | Ethical Hacking & Cyber Security Lab | Lab | 1 | Penetration Testing Tools, Vulnerability Assessment, Forensics Basics, Cryptographic Attacks, Security Auditing |
| BTPE705T | Computer Vision (Professional Elective - IV) | Elective | 3 | Image Processing Fundamentals, Feature Extraction, Object Detection, Image Segmentation, Deep Learning for Vision |
| BTPE706P | Computer Vision Lab | Lab | 1 | OpenCV Library Usage, Image Manipulation, Object Detection Implementation, Face Recognition Systems, Visual Analytics |
| BTPW707P | Major Project - Part I | Project | 4 | Project Proposal, Literature Review, System Design, Initial Prototype Development, Feasibility Study |
Semester 8
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BTPE801T | Internet of Things (Professional Elective - V) | Elective | 3 | IoT Architecture, Sensors and Actuators, Communication Protocols, IoT Platforms, Data Analytics in IoT |
| BTPE802P | Internet of Things Lab | Lab | 1 | Sensor Interfacing, Microcontroller Programming, Cloud Communication, IoT Device Management, IoT Application Development |
| BTPE803T | Blockchain Technology (Professional Elective - VI) | Elective | 3 | Cryptography Basics, Distributed Ledger Technology, Blockchain Architecture, Smart Contracts, Consensus Mechanisms |
| BTPE804P | Blockchain Technology Lab | Lab | 1 | Smart Contract Development, Blockchain Platform Interaction, Cryptocurrency Wallets, Decentralized Application (DApp) Creation, Transaction Security |
| BTPW805P | Major Project - Part II | Project | 7 | Final Project Development, System Integration, Testing and Validation, Comprehensive Documentation, Project Presentation |
| BTPW806P | Internship | Project | 2 | Industry Exposure, Practical Skill Application, Professional Development, Report Writing, Company Culture Immersion |
