Hello everyone my name is Tejas and welcome to the my India jobs website in this blog post I am providing a detailed overview of diploma in computer engineering 6 semester syllabus.
Friends if you are pursuing Diploma in Computer engineering computer science information technology This post is for you it will help you a lot.
So guys in 6th semester is there are some Important subjects which is related to the Engineering’s perspective.
There are total 9 subjects don’t worry guys there are some elective subjects in these semesters also.
As we see in the last semester there are Electives offered by the MSBTE.
Also In this semester There are different Subjects Provided by the MSBTE. Either you have to choose or it is chosen by the college.
It will totally depend on the college to college. In this semester the open elective subjects are digital forensics and hacking techniques, Machine learning, and Network and information security.
Machine learning is my favorite subject in this semester because you will actually learn about how machine learning Works Also You know that ChatGPT, Gemini, Grock, DeepSeek these are the tools Using the Machine Learning.
Which is your favorite subject ? Answer in the comment section which is available on the website.
List of 6th Semester Compute Engineering K scheme Subjects
MSBTE 315301 MANAGEMENT Computer Engineering Syllabus
Unit – I Introduction to Management
1.1 Evolution of management thoughts from ancient/medieval to modern times in India (IKS)
1.2 Management: meaning, importance, characteristics, functions & challenges.
1.3 Introduction to scientific management- Taylor’s & Fayol’s principles of management
1.4 Levels & functions of management at supervisory level.
1.5 Self management skills: Self awareness, self discipline, self motivation, goal setting, time management, decision making, stress management, work life balance and multitasking
1.6 Overview of Managerial Skills: negotiation skills, team management, conflict resolution, feedback, leadership
Unit – II Product, Operations and Project Management
2.1 Creativity and innovation management: creativity techniques – brainstorming, checklist, reverse brainstorming, morphological analysis, six thinking hats.
2.2 New product development, change management
2.3 Product Management -meaning, strategic steps for sustainable design of a product
2.4 Agile product management- concept, benefits, principles and manifesto
2.5 Project Management: importance, areas within project management,4Ps and phases
2.6 Tools of Project Management: PERT and CPM, GANTT & Chart Overview of Estimate and Budget
Unit – III Management Practices
3.1 Quality circle, kaizen, Six Sigma, TQM
3.2 5S, Kanban card system, TPM, Lean Manufacturing: Meaning, Steps and Importance
3.3 Quality Standards and ISO: Meaning, ISO 9001:2016, ISO 14000, OSHA 2020
3.4 The overview of ERP along with example
3.5 Service quality and customer/client satisfaction, service scape
Unit – IV Marketing Management
4.1 Marketing management: meaning, significance, Seven P’s of Marketing
4.2 Needs, wants and demands in marketing. Customer relationship management
4.3 Types of marketing: traditional and digital marketing
4.4 Event management: types, different aspects of event management, crisis management
Unit – V Supply Chain & Human Resource Management
5.1 The overview of Supply Chain and logistics Management
5.2 Components of Supply Chain and logistics Management
5.3 Role of information technology in supply chain & logistics management
5.4 Overview of Human Resource Management-Meaning, significance, scope and principles
5.5 Recruitment, selection and training of human resources. Chalk Circle
5.6 Qualities of a successful supervisor /team leader and types of leadership
MSBTE 316313 EMERGING TRENDS IN COMPUTER ENGINEERING AND INFORMATION TECHNOLOGY Syllabus
Unit – I Introduction of AI and ML
1.1 Introduction of AI :Concept ,Scope of Al, Types of AI, Applications of AI
1.2 Machine Learning: Concept, Types: Supervised, Unsupervised, Reinforcement, Applications of Machine Learning, Concept of Deep Learning, Applications of Deep Learning ,Concept of Neural Network, Difference between AI, ML and DL
1.3 Generative AI: Concept ,Transformers: Key components of Transformers: Self-attention mechanism, Multi-head attention, Positional encoding, Feed forward Neural Network, Layer Normalization, Encoder Decoder Structure, Types of Generative AI: Text Generation, Image Generation, Music and Audio Generation, Video Generation ,Applications of Generative AI
1.4 AI & ML in Digital security :Types of attacks : AI Powered cyber attack, Adversarial AI attacks, Evasion AI Attack, AI poisoning attack, AI powered attacks protection measures: Turn on Multi-Factor Authentication, Use Super Strong Password, Update Everything, Secure your Network, Use your mobile Device Securely
Unit – II Internet of Things
2.1 Introduction of Internet of Things (loT): Definition, Characteristics of loT, Features and Application of loT, Advantages and limitations of IoT
2.2 Design of loT: Physical design of IoT, Logical design of loT, Architecture of Internet of Things (IoT)
2.3 Sensors and actuators used in IoT
2.4 5G Network in IOT communication: 5-G characteristics and application areas, Next Generation Network: Architecture, Features, Functional block diagram, Network components: Media Gateway, Media Gateway Controller and Application Server
2.5 IoT and Cloud Computing: Architecture of Cloud based IoT
Unit – III Blockchain Technology
3.1 Basics of Blockchain Technology-Definition, Key Features of Blockchain (Decentralization, Transparency, Immutability),Traditional vs Blockchain System
3.2 Blockchain Architecture
3.3 Types of Blockchain- Public Blockchain, Private Blockchain, Consortium Blockchain and Hybrid Blockchain
3.4 Blockchain Applications- Finance, Healthcare, Supply chain and Gaming
3.5 Role of Blockchain in Smart Contracts & Cryptocurrencies – Definition, Key Features of Smart Contracts, Popular Cryptocurrencies
3.6 Challenges in Blockchain Technology
Unit – IV Immersive Technology and Sustainable Computing
4.1 Introduction to Immersive Technology and types of immersive technologies- Augmented Reality (AR), Virtual Reality (VR), Mixed Reality (MR), Extended Reality (XR), Haptic Technology
4.2 Applications of Immersive Technology
4.3 Green Computing- Definition and its importance, Energy efficient hardware and data centers. E-waste management and recycling
4.4 Quantum Computing- Introduction, Applications
Unit – V Digital Forensics and Ethical Hacking
5.1 Introduction to digital forensics
5.2 Rules of digital forensics, The Process of Digital forensics investigation and Evidence Handling
5.3 Models of Digital Forensic Investigation: DFRWS Investigative Model, Abstract Digital Forensics Model (ADFM) ,Integrated Digital Investigation Process (IDIP), End to End digital investigation process (EEDIP) , An extended model for cybercrime investigation, UML modeling of digital forensic process model (UMDFPM)
5.4 Ethical Hacking: Definition, Types of hackers
5.5 Types of Hacking- Network Hacking: AI powered phishing scams, Ransomware 2.0, IoT exploits , Deep fake Technology, Operating System Hacking- OS downgrade attack, Firmware level exploits, Application Hacking- Advanced Web Application Firewall(WAF) Bypass Technique, Zero day exploits
5.6 National Cyber Security Policy (NCSP), 2013 ,IT Act 2000, IT Act 2008(Amendment) and IT Act 2023(DPDP),Cyber Crime Prevention against Women and Children (CCPWC) Scheme (2018)
MSBTE 316314 SOFTWARE TESTING Syllabus
Unit – I Software Testing and Testing Methods
1.1 Software Testing, Objectives of Testing, Software Requirement Specification (SRS)
1.2 Failure, Error, Fault, Defect, Bug Terminology
1.3 Test Case, Entry and Exit Criteria for Testing
1.4 Methods of Testing: Static and Dynamic Testing
1.5 White Box Testing: Inspections, Walkthroughs, Technical Review, Functional Testing, Code Coverage Testing, Code Complexity Testing
1.6 Black Box Testing: Requirement Based Testing, Boundary Value Analysis and Equivalence Partitioning
Unit – II Types and Levels of Testing
2.1 Unit Testing: Driver, Stub
2.2 Integration Testing: Top-Down Integration, bottom-Up Integration, Bi-Directional Integration
2.3 System Testing
2.4 Acceptance Testing: Alpha, Beta Testing
2.5 Special Testing: Performance Testing-Load Testing and Stress Testing, Regression Testing, Security Testing, Client-Server Testing, GUI Testing, Database Testing, Sanity and Smoke Testing”
Unit – III Test Management
3.1 Test life cycle
3.2 Test Planning: Preparing a Test Plan, Deciding the Test Approach, Setting Up Criteria for Testing, Identifying Responsibilities, Staffing, Resource Requirements, Test Deliverables, Testing Tasks
3.3 Test Management: Test Infrastructure Management, Test People Management
3.4 Test Process: Base Lining a Test Plan, Test Case Specification
3.5 Test Reporting: Executing Test Cases, Preparing Test Summary Report
Unit – IV Defect Management
4.1 Defect Classification, Defect Management Process
4.2 Defect Life Cycle, Defect Template
4.3 Estimate Expected Impact of a Defect, Techniques for Finding Defects, Reporting a Defect
Unit – V Testing Tools and Measurements
5.1 Manual Testing verses Automation Testing, advantages and disadvantages of using Testing Tools
5.2 Selecting a Test Tool: Criteria for Selecting Test Tools, Steps for Tool Selection and Deployment
5.3 Selenium: Introduction and Components, Automation Testing Tools
5.4 Selenium IDE: Introduction, Features, Limitations
5.5 Selenium WebDriver: Introduction, advantages and disadvantages
5.6 Metrics and Measurement: Types of Metrics, Product Metrics and Process Metric
MSBTE 316005 CLIENT SIDE SCRIPTING Syllabus
Unit – I Fundamental of Client Side Scripting
1.1 Introduction to the Scripting: Basic web architecture, Role of the client and server, Static vs. dynamic web pages
1.2 History of Scripting Technologies: HTML as a foundation, Early use of inline scripting, Limitations of static HTML, JavaScript
1.3 Introduction to AJAX : AJAX Architecture, Actions
1.4 Basics of JSON: Objects, Scheme
1.5 Webpage with Python: Django and Flask framework
Unit – II Angular Basics
2.1 Introduction to AngularJS: AngularJS Extends HTML, Expressions, MVC Architecture, Application in AngularJs, Variables Scope
2.2 AngularJS Forms: FORM tag, Form fields: Single line text field, password field, multiple line text area, radio buttons, and check boxes. Pull down menus: SELECT and OPTION tags. Buttons: submit, reset and generalized buttons, Form Validation
2.3 AngularJS Data Binding :Two-way Binding and ng-model directive
2.4 Filters: Built-In Filters, Custom Filter, Chaining Multiple Filters
2.5 AngularJS Events: ng-mousedown, ng-mouseup, ng-click
Unit – III Working with AngularJS
3.1 AngularJS Tables: Display Data in a Table, Adding style to the Table data, orderBy Filter, uppercase Filter, Table Index, using $even and $odd
3.2 AngularJS Controllers: Initializing the Model with Controllers, Role of a Controller, Controllers & Modules, Controller Business Logic, Presentation Logic and Formatting Data
3.3 Attaching Properties and functions to scope
3.4 Nested Controllers, Using Filters in Controllers
3.5 Controllers in External Files
Unit – IV Introduction of React Framework
4.1 Introduction to React Framework, features, architecture & Form
4.2 Components: Functional components, Class components, Passing and using props
4.3 Lifecycle – Mounting, Updating and Unmounting
4.4 React Hooks – useState,useEffect, useContext
Unit – V Working with React Framework
5.1 Event handling, Binding event handlers, Arrow functions vs. regular functions
5.2 Working with Forms – Adding components, Handling form, Submitting Forms, Form validation
5.3 Lists and Keys – Rendering Lists, List with Key, Using map() to render lists of elements
5.4 Cascading Style Sheets- Different types of Style Sheets, Styling Libraries, Popular CSS frameworks (e.g., Bootstrap, Material-UI)
MSBTE 316006 MOBILE APPLICATION DEVELOPMENT Syllabus
Unit – I Basics of Android OS
1.1 Introduction to Android Operating System
1.2 Need and features of Android
1.3 Android Architecture Framework
1.4 Introduction to Android Application Development IDE (Android Studio, Eclipse, Visual Studio with Xamarin etc.)
Unit – II Introduction to Android Environment
2.1 Use of Java JDK and introduction to Android SDK
2.2 Different Android tools like Android Development Tools (ADT), Android Virtual Devices (AVD) and emulators
2.3 Dalvik Virtual Machine (DVM) , difference between DVM and JVM
2.4 Terminologies in Android : Android Run Time (ART), Over the Air (OTA), Firmware Over The Air (FOTA), Global Positioning System (GPS) , Google Cloud Messaging (GCM)
2.5 Android directory structure
Unit – III Design UI in Android
3.1 GUI components like : Text View, Edit Text, Button, types of buttons like image button , toggle button, Checkbox, Radiobutton, Radiobutton Group, Progress bar, Scrollbars, List, Custom Toast Alert message etc.
3.2 Introduction to Layouts and types of Layouts : Constraint layout, Linear Layout, Frame Layout, Relative Layout etc.
3.3 Introduction to views and its types : List view, Grid view, Image view, Scroll view
3.4 Basics of splash screen , adding styles to splash screen
Unit – IV Android Components and Database Connectivity
4.1 Major components in Android : Intent, Activity, Services, Broadcast Receiver
4.2 Life cycle of Android components like Activity, Broadcast Receiver, Services etc.
4.3 SQLite/Firebase database, necessity of SQLite/Firebase, creation and connection of the database, extracting data from the databases
Unit – V Android Application Deployment
5.1 Advanced Concepts : Fragments,Location based services, SMS telephony, Audio capture, Camera, Bluetooth etc.
5.2 Security Concepts : Android security model, declaring and using permissions, using custom permission
5.3 Application Deployment : Process for creating and deploying Android applications on Google Play store, become a publisher
MSBTE 316315 DIGITAL FORENSIC AND HACKING TECHNIQUES Syllabus
Unit – I Digital Forensics
1.1 Overview of Digital forensics, Rules of digital forensic, Digital forensics investigation and its goal
1.2 Introduction to Cyber Crime and attack
1.3 Types of Digital Forensics- Computer Forensics, Network Forensics, Cloud Forensics, Mobile Forensics and Database Forensics
1.4 Digital Forensics process
1.5 Areas of Applications of computer forensics- Public Sector, Private Sector
Unit – II Digital Forensic Investigation Models
2.1 Models of Digital Forensic Investigation: DFRWS Investigative Model, Abstract Digital Forensics Model (ADFM), Integrated Digital Investigation Process (IDIP), End-to-End digital investigation process (EEDIP), An extended model for cybercrime investigation, UML modeling of digital forensic process model (UMDFPM)
2.2 Challenges in Digital Forensics: Encryption, Volume of Data, Anti-Forensics Techniques, Legal and Ethical Issues, Emerging Technologies
2.3 Legal and Ethical Considerations in Digital Forensics: General ethical norms for investigators, Unethical norms for investigation
Unit – III Digital Evidences
3.1 Crime Scenes and Collecting Evidence-Removable Media, Cell Phones, Order of Volatility
3.2 Documenting the Scene-Photography, Notes
3.3 Chain of Custody-Marking Evidence
3.4 Cloning-Purpose of Cloning, The Cloning Process, Forensically Clean Media, Forensic Image Formats, Risks and Challenges
3.5 Live System versus Dead System-Live Acquisition Concerns, Advantage of Live Collection, Principles of Live Collection, Conducting and Documenting a Live Collection
3.6 Hashing-Types of Hashing Algorithms, Hashing Example, Uses of Hashing
Unit – IV Basics of Hacking
4.1 Ethical Hacking: How Hackers Beget Ethical Hackers, Defining hacker, Malicious users
4.2 Understanding the need to hack your own systems
4.3 Understanding the dangers your systems face: Nontechnical attacks, Network-infrastructure attacks, Operating-system attacks, Application and other specialized attacks
4.4 Obeying the Ethical hacking Principles: Working ethically, Respecting privacy, Not crashing your systems
4.5 Ethical hacking Process: Formulating plan, Selecting tools, Executing the plan, Evaluating results
Unit – V Hacking Techniques
5.1 Overview of Ethical Hacking and Penetration Testing
5.2 Phases of Ethical Hacking: Reconnaissance, Scanning, Exploitation, Post-Exploitation
5.3 Network Hacking: Network Infrastructure Vulnerabilities, Scanning-Ports, Ping swiping, Scanning SNMP, Grabbing Banners, Analysing Network Data and Network Analyzer, MAC-daddy attack
5.4 Introduction to Social Engineering, Types of social engineering attacks- Phishing, Watering hole attacks, Physical social engineering
MSBTE 316316 MACHINE LEARNING Syllabus
Unit – I Introduction to Machine Learning
1.1 Basics of ML – Define Machine Learning, Traditional programming vs ML-based approaches, Role and application of ML in artificial intelligence and data science
1.2 Types of ML (Supervised, Unsupervised, Reinforcement Learning)-Supervised Learning: Definition, working principle, examples (classification, regression), Unsupervised Learning: Definition, working principle, examples, Clustering, dimensionality reduction techniques, Reinforcement Learning: Concept of agents, rewards, and policy learning, Comparison of different ML types with real-world applications
1.3 Applications of ML- Real-world use cases of ML in various domains such as healthcare, finance, e-commerce, etc, challenges in Machine Learning
1.4 Introduction to Python for ML-Basics of Python programming relevant to ML, Overview required libraries: NumPy, Pandas, Matplotlib, Scikit-learn, Writing and executing simple ML scripts in Python
Unit – II Data Preprocessing
2.1 Data Cleaning :Introduction to Data Cleaning, Identifying and Handling Noisy Data, Removing Duplicates and Inconsistencies, Standardizing and Normalizing Data, Handling Outliers
2.2 Handling Missing Values -Types of Missing Data, Identifying Missing Values, Techniques to Handle Missing Data, Removing Missing Data, Mean, Median, and Mode Imputation, Predictive Imputation (Regression, KNN), Using Algorithms that Support Missing Values
2.3 Splitting Dataset for Training and Testing -Importance of Dataset Splitting, Train-Test Split Ratio Selection, Cross-Validation Techniques, K-Fold Cross Validation, Leave-One-Out Cross Validation, Stratified Sampling vs Random Sampling
Unit – III Feature Selection
3.1 Feature Scaling and Selection-Importance of Feature Scaling, Normalization vs Standardization, Feature Selection Methods, Filter Methods (Correlation, Chi-Square), Wrapper Methods (Forward, Backward Selection), Embedded Methods (Lasso, Decision Trees)
3.2 Feature Extraction Techniques – Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA)
3.3 Mutual Information-Based Feature Selection, ANOVA (Analysis of Variance) for Feature Selection, Recursive Feature Elimination (RFE) with Cross-Validation (RFECV), Feature Importance from Tree-Based Models (Beyond Decision Trees), XGBoost, LightGBM, Random Forest provide built-in feature importance scores (Gini importance, SHAP values).
Unit – IV Supervised Learning
4.1 Classification Algorithms: Decision Trees, KNN(K-Nearest Neighbors), SVM(Support Vector Machine)
4.2 Regression Algorithms: Linear Regression, Logistic Regression, Ridge Regression
4.3 Model Performance Evaluation: Confusion Matrix, Accuracy, Precision, Recall
Unit – V Unsupervised Learning
5.1 Clustering Techniques:-Define Clustering, Importance of clustering in data analysis, Applications of Clustering
5.2 K-Means Clustering: Definition and working principle, Steps involved in the K-Means algorithm, Advantages of K-Means, Disadvantages of K-Means, Hierarchical Clustering: Definition and types, Steps in Hierarchical Clustering, Advantages of Hierarchical Clustering, Disadvantages of Hierarchical Clustering, Comparing K-Means and Hierarchical Clustering
5.3 Dimensionality Reduction: Importance of Dimensionality Reduction
5.4 PCA -Definition and fundamental principles of PCA, Eigenvectors and eigenvalues, Steps in PCA, Explained Variance, Choosing the Optimal Dimensionality, Advantages and Disadvantages of PCA, Applications of PCA
MSBTE Syllabus
Unit – I Introduction to Computer and Information Security
1.1 Foundations of computer security: Definition and Need of Computer Security, Security Basics: Confidentiality, Integrity, Availability, Accountability, Authentication, Non – repudiation and Reliability
1.2 Information Security Overview: Introduction to information, need and importance of information security, Information classification, Criteria for information classification
1.3 Type of Attacks: Active and Passive attacks, Masquerade Attack, Denial of Service, Backdoors and Trapdoors, Sniffing, phishing, Spoofing, Man in the Middle, Replay, TCP/IP Hacking, Social Engineering
1.4 Types of Malwares: Virus, Worms, Trojan horse, Spyware, Adware, Ransom ware, Logic Bombs, Rootkits, Key loggers
1.5 Operating system updates: HotFix, Patch, Service Pack
1.6 Threat to security: Introduction to assets, vulnerability, threats, risks, relation between threat, vulnerability, risks
Check out – Diploma in Computer Engineering 5th Semester K Scheme Syllabus with Subtopics
Unit – II User Authentication and Access Control
2.1 Identification and Authentication methods: Electronic user authentication, user name and password, multi-factor authentication, token-based authentic
2.2 Password attacks: Guessing password, Piggybacking, Shoulder surfing, Dumpster diving
2.3 Biometrics: Finger prints, Hand prints, Retina scan patterns, Voice patterns, Face recognition, Signature and Writing patterns, Keystrokes
2.4 Authorization: Introduction to authorization, goals of authorization
2.5 Access controls: Definition, Authentication mechanism, Access control principles, Access rights and permission Access control policies: Discretionary access control (DAC), Mandatory access control (MAC), Role-based access control(RBAC),Attribute-based access control (ABAC)
Unit – III Cryptography
3.1 Introduction: Plain text, Cipher text, Cryptography, Cryptanalysis, Cryptology, Encryption, Decryption
3.2 Symmetric and Asymmetric cryptography : Introduction, working, key management, asymmetric cryptography -public key distribution
3.3 Substitution techniques : Caesar cipher, Play fair cipher, Vigenere cipher, Vernam cipher(One-timepad)
3.4 Transposition techniques: Railfence technique, Simple columnar technique
3.5 Steganography: Overview of steganography
Unit – IV Firewall and Encryption Algorithms
4.1 Firewall: Need of firewall, Types of firewalls: Packet filters, Stateful packet filters, Application gateways, Circuit gateways
4.2 Firewall policies, Configuration, Limitations, Demilitarized zone (DMZ)
4.3 DES (Data Encryption Standard) algorithm, AES (Advanced Encryption Standard) algorithm, RSA (Rivest-Shamir-Adleman) algorithm
4.4 Diffie-Hellman key exchange algorithm, Man-in- middle attack
4.5 Hash Function: Introduction, Features of Hash Functions, MD5 (Message Digest Method 5) and SHA(secure hashing algorithm) algorithm
4.6 Digital Signature: Introduction and working of digital signature, Digital Certificate
Unit – V Network and Database Security
5.1 Intrusion Detection System(IDS):Network-based IDS, Host-based IDS, Honeypots
5.2 Kerberos: Working, Authentication Server (AS), Ticket Granting Service (TGS), Service Server (SS), IP Security: Overview, Authentication Header (AH), Encapsulating Security Payload (ESP) protocols, Transport and tunnel modes
5.3 E-mail security: Simple mail transfer protocol (SMTP), Pretty good privacy (PGP), Secure/Multipurpose Internet Mail Extensions (S/MIME), Privacy Enhance Mail (PEM)
5.4 Database Security: Need for database security, SQL injection attack, database encryption
5.5 Cloud security: Essential characteristics, service model, deployment model, cloud specific security threats
Conclusion
Show guys in this post we had seen MSP tiploma computer engineering 6 semester complete syllabus with subtopics.
So we had completed the Computer engineering syllabus from first semester up to the 6th semester.
In upcoming post Complete civil engineering Syllabus With subtopics and weightage of each unit.
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I have given the link because you can refer the Official deaths of the timetable Add exam form updates related to your academic year.
Instead of trusting on any website you should trust on the official website first then you can trust Other website.
So thank you very much for visiting this post and giving your precious time on our post In upcoming post we will share all the materials related to the computer engineering and all the branches says syllabus are coming soon.
Have a good day !