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RGPV B.Tech · 4th Year

AIML 8th Semester Syllabus

Artificial Intelligence & Machine Learning (AIML): the official syllabus of all 9 8th sem subjects, unit by unit, with previous year papers, notes and important questions. Free to read.

Subjects

AIML 8th semester syllabus, unit by unit

Every subject of RGPV Artificial Intelligence & Machine Learning 8th semester (4th year), as the official syllabus lists it.

Business Intelligence (BI)

AL-801

  1. Unit 1Business Intelligence

    Effective and timely decisions · Data, information and knowledge · Role of mathematical models · Business intelligence architectures · Cycle of a business intelligence analysis · Enabling factors in business intelligence projects · Development of a business intelligence system · Ethics and business intelligence

  2. Unit 2Knowledge Delivery

    The business intelligence user types · Standard reports · Interactive analysis and ad‑hoc querying · Parameterized reports and self‑service reporting · Dimensional analysis · Alerts/notifications · Visualization: charts, graphs, widgets, scorecards and dashboards · Geographic visualization · Integrated analytics · Optimizing the presentation for the right message

  3. Unit 3Efficiency

    Efficiency measures · CCR model – definition of target objectives, peer groups, identification of good operating practices · Cross‑efficiency analysis – virtual inputs and outputs, other models · Pattern matching – cluster analysis, outlier analysis

  4. Unit 4Business Intelligence Applications

    Marketing models · Logistic and production models · Case studies

  5. Unit 5Future of Business Intelligence

    Emerging technologies · Machine learning · Predicting the future · BI search & text analytics · Advanced visualization · Rich reporting · Future beyond technology

Block Chain Technologies (BCT)

AL-802 (A)

  1. Unit 1Introduction: Overview of Block chain

    Public Ledgers · Bitcoin · Smart Contracts · Block in a Block chain · Transactions · Distributed Consensus · Public vs Private Block chain · Understanding Cryptocurrency to Block chain · Permissioned Model of Block chain · Overview of Security aspects of Block chain · Cryptographic Hash Function · Properties of a hash function · Hash pointer and Merkle tree · Digital Signature · Public Key Cryptography · A basic cryptocurrency

  2. Unit 2Understanding Block chain with Crypto currency

    Creation of coins · Payments and double spending · Bitcoin Scripts · Bitcoin P2P Network · Transaction in Bitcoin Network · Block Mining · Block propagation and block relay · Distributed consensus in open environments · Consensus in a Bitcoin network · Proof of Work (PoW) – basic introduction · HashCash PoW · Bitcoin PoW · Attacks on PoW and the monopoly problem · Proof of Stake · Proof of Burn · Proof of Elapsed Time · Life of a Bitcoin Miner · Mining Difficulty · Mining Pool

  3. Unit 3Understanding Block chain for Enterprises

    Permissioned model and use cases · Design issues for Permissioned block chains · Execute contracts · State machine replication · Distributed consensus in closed environment · Paxos · RAFT Consensus · Byzantine general problem · Byzantine fault tolerant system · Lamport-Shostak-Pease BFT Algorithm · BFT over Asynchronous systems

  4. Unit 4Enterprise application of Block chain

    Cross border payments · Know Your Customer (KYC) · Food Security · Mortgage over Block chain · Block chain enabled Trade · We Trade – Trade Finance Network · Supply Chain Financing · Identity on Block chain

  5. Unit 5Block chain application development

    Hyperledger Fabric – Architecture · Identities and Policies · Membership and Access Control · Channels · Transaction Validation · Writing smart contract using Hyperledger Fabric · Writing smart contract using Ethereum · Overview of Ripple · Overview of Corda

High Performance computing (HPC)

AL-802 (B)

  1. Unit 1Introduction to modern processors

    General purpose cache based architecture · Performance metrics and benchmarks · Moore's Law · Pipelining · Superscalar execution · SIMD · Memory hierarchies · Multi‑core processors · Multi‑threaded processors · Vector processor design principles · Maximum performance estimates · Programming for vector architecture · Scalar profiling · Common‑sense optimizations · Simple measures and their impacts · Role of compilers · C++ optimizations

  2. Unit 2Data access optimizations and Parallel Computers

    Balance analysis and light‑speed estimates · Storage order · Algorithm classifications and assessment optimizations · Case studies for data‑access optimizations · Shared memory computers · Distributed memory computers · Hybrid systems · Network computers

  3. Unit 3Basics of parallel computing and OpenMP programming

    Data parallelism · Functional parallelism · Parallel scalability laws · Parallel scalability metrics · Factors affecting scalability · Efficiency and load imbalance · Shared memory parallel programming with OpenMP · Parallel execution · Data scoping · Work sharing using loops · Synchronization · Reductions · Loop scheduling · Tasking

  4. Unit 4Efficient OpenMP Programming

    Program profiling · Performance pitfalls · Improving impact of OpenMP work‑sharing constructs · Determining overheads for short loops · Serialization · False sharing

  5. Unit 5Distributed Memory parallel programming with MPI

    Message passing interface (MPI) · Point‑to‑point communication · Collective communication · Non‑blocking point‑to‑point communication · Virtual topologies · MPI performance tools · Communication parameters · Impact of synchronizations, sterilizations and contentions · Reductions in communication overhead

Big Data Analytics (BDA)

AL-802 (C)

  1. Unit 1Introduction to Big Data

    Big data characteristics · Types of big data · Traditional versus big data · Evolution of big data · Challenges with big data · Technologies available for big data · Infrastructure for big data · Use of data analytics · Desired properties of big data systems

  2. Unit 2Introduction to Hadoop

    Core Hadoop components · Hadoop ecosystem · Hive physical architecture · Hadoop limitations · RDBMS versus Hadoop · Hadoop Distributed File System (HDFS) · Processing data with Hadoop · Managing resources and applications with Hadoop YARN · MapReduce programming

  3. Unit 3Hive and Pig

    Hive architecture · Hive data types · Hive Query Language (HQL) · Introduction to Pig · Anatomy of Pig · Pig on Hadoop · Use case for Pig · ETL processing with Pig · Data types in Pig · Execution model of Pig · Pig operators and functions

  4. Unit 4NoSQL Databases

    Introduction to NoSQL · NoSQL business drivers · NoSQL data architectural patterns · Variations of NoSQL architectural patterns for managing big data · Introduction to MongoDB

  5. Unit 5Mining Social Network Graphs

    Introduction to social network mining · Applications of social network mining · Social networks as graphs · Types of social networks · Clustering of social graphs · Discovery of communities in a social graph · Introduction to recommender systems

Quantum Computing (QC)

AL-802 (D)

  1. Unit 1Motivation for studying Quantum Computing

    Major players in the industry (IBM, Microsoft, Rigetti, D-Wave etc.) · Origin of Quantum Computing · Overview of major concepts in Quantum Computing: Qubits and multi-qubits states · Braket notation · Bloch Sphere representation · Quantum Superposition · Quantum Entanglement

  2. Unit 2Math Foundation for Quantum Computing

    Matrix Algebra: basis vectors and orthogonality · Inner product and Hilbert spaces · Matrices and tensors · Unitary operators and projectors · Dirac notation · Eigen values and Eigen vectors

  3. Unit 3Building Blocks for Quantum Program

    Architecture of a Quantum Computing platform · Details of q-bit system of information representation: Block Sphere · Multi-qubits States · Quantum superposition of qubits (valid and invalid superposition) · Quantum Entanglement · Useful states from quantum algorithmic perspective e.g. Bell State · Operation on qubits: Measuring and transforming using gates · Quantum Logic gates and Circuit: Pauli · Hadamard · Phase shift · Controlled gates · Ising · Deutsch · Swap etc.

  4. Unit 4Programming model for a Quantum Computing Program

    Steps performed on classical computer · Steps performed on Quantum Computer · Moving data between bits and qubits · Basic techniques exploited by quantum algorithms: Amplitude amplification · Quantum Fourier Transform · Phase Kick-back · Quantum Phase estimation · Quantum Walks

  5. Unit 5Major Algorithms and Toolkits

    Shor’s Algorithm · Grover’s Algorithm · Deutsch’s Algorithm · Deutsch‑Jozsa Algorithm · OSS Toolkits for implementing Quantum program: IBM quantum experience · Microsoft Q · Rigetti PyQuil (QPU/QVM)

Introduction to IOT (II)

AL-803 (A)

  1. Unit 1IoT definition

    Characteristics · IoT conceptual and architectural framework · Components of IoT ecosystems · Physical and logical design of IoT · IoT enablers · Modern day IoT applications · M2M communications · IoT vs M2M · IoT vs WoT · IoT reference architecture · IoT Network configurations · IoT LAN · IoT WAN · IoT Node · IoT Gateway · IoT Proxy · Review of Basic Microcontrollers and interfacing

  2. Unit 2Define Sensor

    Basic components and challenges of a sensor node · Sensor features · Sensor resolution · Sensor classes: Analog, Digital, Scalar, Vector Sensors · Sensor Types, bias, drift, Hysteresis error, quantization error · Actuator · Actuator types: Hydraulic, Pneumatic, electrical, thermal/magnetic, mechanical actuators, soft actuators

  3. Unit 3Basics of IoT Networking

    IoT Components · Functional components of IoT · IoT service oriented architecture · IoT challenges · 6LoWPAN · IEEE 802.15.4 · ZigBee and its types · RFID Features · RFID working principle and applications · NFC (Near Field Communication) · Bluetooth · Wireless Sensor Networks and its Applications

  4. Unit 4MQTT

    MQTT methods and components · MQTT communication · Topics and applications · SMQTT · CoAP · CoAP message types · CoAP Request-Response model · XMPP · AMQP features and components · AMQP frame types

  5. Unit 5IoT Platforms

    Arduino · Raspberry Pi Board · Other IoT Platforms · Data Analytics for IoT · Cloud for IoT · Cloud storage models & communication APIs · Attacks in IoT system · Vulnerability analysis in IoT · IoT case studies: Smart Home, Smart framing etc.

Bio Informatics (BI)

AL-803 (B)

  1. Unit 1Introduction

    Introduction to bioinformatics · Objectives of bioinformatics · Basic chemistry of nucleic acids · Structure of DNA & RNA · Genes · Structure of bacterial chromosome · Cloning methodology · Data maintenance and integrity tasks

  2. Unit 2Bioinformatics Databases & Image Processing

    Types of databases · Nucleotide sequence databases · Protein sequence databases · Protein structure databases · Normalization · Data cleaning and transformation · Protein folding · Protein function · Protein purification and characterization · Introduction to Java clients · CORBA · Using MYSQL · Feature extraction

  3. Unit 3Sequence Alignment and Database Searching

    Introduction to sequence analysis · Models for sequence analysis · Methods of optimal alignment · Tools for sequence alignment · Dynamic programming · Heuristic methods · Multiple sequence alignment

  4. Unit 4Gene Finding and Expression

    Cracking the genome · Biological decoder ring · Finding genes through mathematics and learning · Gene prediction tools · Gene mapping · Application of mapping · Modes of gene expression data · Mining gene expression data

  5. Unit 5Proteomics & Problem Solving in Bioinformatics

    Proteome analysis · Tools for proteome analysis · Genetic networks · Network properties and analysis · Complete pathway simulation (E‑cell) · Genomic analysis for DNA & protein sequences · Strategies and options for similarity search · Flowcharts for protein structure prediction

Managing Innovation and Entrepreneurship (MIE)

AL-803 (C)

  1. Unit 1Innovation – definition, classification and relationship with entrepreneurship

    Definition and classification of innovation · Relationship between innovation and entrepreneurship · Creation of competitive advantage through innovation · Innovative models · Product innovation · Process innovation · Organizational innovation · Marketing innovation · Role of innovations in business development

  2. Unit 2Sources and creative methods for innovation management

    Sources of innovation: push, pull, analogies · Technology transfer · Creative methods and approaches used in innovation management · Agile management approach · Six Thinking Hats technique · NUF test method

  3. Unit 3Project‑based innovation management and open innovation

    Project approach to innovation management · Stage‑Gate method and its essence · Adaptation of Stage‑Gate to selected business models · In‑house business development of the innovation process · Open Innovation concept · Limits and benefits of Open Innovation

  4. Unit 4Human‑centered innovation and co‑creation strategies

    Innovations aimed at humans · Role of co‑creation in the innovation process · Innovation process strategies · Types of innovation strategies · Selection of appropriate strategies

  5. Unit 5Measurement, barriers and facilitation of innovation

    Measurement and evaluation of innovation benefits for business · Financial and non‑financial metrics for innovation · Combination and choice of metrics · Barriers to innovation in business · Causes of innovation failure · Post‑audit of innovative projects · Organization and facilitation of an innovation workshop

Human Computer Interaction (HCI)

AL-804 (D)

  1. Unit 1Introduction

    Human Computer Interaction (HCI) concepts and definitions · Nature of interaction human and Machine · Interaction design · Understanding and conceptualizing interaction · Understanding users, interfaces and interactions · Data gathering

  2. Unit 2Introduction to User Centered System Design (UCSD) and related concepts

    User Centered System Design (UCSD) · Natural computing · Core concepts of user centered system design · Interactive design and its strengths and weaknesses · Types of user model · User model evaluation · Heuristic evaluation

  3. Unit 3Psychological User Models and Quantitative Performance Analysis

    Psychological user models · Black‑box models of human performance (perception, motor control, memory, problem‑solving) · Quantitative analysis of performance · Human processor · Keystroke Level Model (KLM) · GOMS descriptions of user performance

  4. Unit 4Modeling, Prototyping, and Evaluation Techniques

    Modeling of system understanding · Mental models and metaphor · Use of design prototypes · Controlled experiments · Cognitive walkthrough · Evaluation from the perspective of a novice learner

  5. Unit 5Task Analysis, Design, and Emerging Interaction Paradigms

    Task analysis and design · Contextual and qualitative studies · Use‑case driven design · Research techniques · Cognitive dimensions of notations · Computer‑Supported Cooperative Work (CSCW) · Ubiquitous computing · New interaction techniques · Programmability