NECentreOfExcellence Courses details

Courses:

1.    Certificate Course in IoT


Module Details

  • IOT Architecture, building blocks
  • Things in IOT, Terminology
    - end nodes/sensor nodes
    - gateways
    - servers/cloud platforms
  • Applications of IOT
  • Standards, history
  • IOT-A Reference model, architecture
  • Enabling technologies
  • Talking to environments
    -available sensors,actuators
    - sensor nodes
    - connectivity solutions
    gateway solutions
    cloud platforms
    Challenges in IOT
    - power optimization, mobility, connectivity, security

NodeJs:
Setting up Nodejs
Simple scripts, console operations
variables, data types, operators
control structures, functions
arrays, string handling
classes & objects
event handling
error handling
package management, importing libraries
NodeRED:
Setting up nodered on target machine
Available nodes, Inject, Debug, significant function nodes
Creating simple flows, sub flows
Writing functions
Importing, Exporting flows
Context management, Storing Data
Adding additional nodes
UI development using NodeRED

  • Setting up python interpreter
  • Simple programs, console i/o operations
  • Data types, variables, literals, operators
  • Conditional branching, loops
  • Arrays & Strings
  • Functions, Modules
  • Package management
  • Regular expressions, pattern matching
  • Error handling
  • Standard Library

  • Architecture of embedded linux – kernel, system calls, libraries
  • Internals – Process, Thread, File Handling
  • Getting familiar with Linux command line
  • Environment Variables
  • Basic Administration
  • Deploying Linux on target board
  • Rootfs image, File System Hiearchy
  • Understanding boot loaders for target boards.
  • System Monitoring & Tracing techniques – procfs, sysfs
  • Package management on Linux
  • Understanding cross tools, Cross compiling applications
Peripheral interfacing using libraries
  • ADC
  • GPIO, PWM
  • UART

  • Network layer model for IOT
  • Physical channels for communication (wired/wireless)
  • IPv4 concepts
  • TCP, UDP Protocols, Socket Programming
  • IEEE 802.11(WLAN)
  • Bluetooth, Bluetooth Low Energy (BLE) – protocols, profiles
  • RFID concepts

M2M vs IOT

Communication models
Request Response
Publish Subscribe
Push Pull
Exclusive Pair
Communication Protocols
- MQTT
- CoAP
- Websockets
- HTTP REST (GET,POST,PUT,DELETE)
Available tools & libraries for above protocols Protocol Bridging, Interoperability

Virtualization concepts, Cloud Architecture, Cloud services -- SaaS, PaaS, IaaS,
Study of IOT Cloud platforms, Supporting protocols and connectivity, Data Visualization, Dashboardss

Introduction to communication, Barriers to communication, Kind of communication, Confidence building Non-verbal Communication, Fluency and vocabulary, Synonyms, Antonyms, Grammar, Noun Pronoun, Verb, Adjective, Preposition, Conjunction, Words of Idioms & phrases, Sentence Construction, Fill up the blanks, Pronunciation, Conversation practice, Polite Conversation, Greeting, Logical reasoning, General Aptitude, Writing: Covering letter, Resume, Email, Presentation Skill, group discussion, Interview skills, Mock interview

2.    Certificate Course in Network Security (CCNS)


Module Details

  • Introduction to computer Networking
  • Categories of Networking according to size (LAN,WAN,DAN,MAN)
  • Types of connections
  • Network classifications (Wired, Wireless )
  • Network Hardware Devices (Hub, Switch, Modem, Router, Bridge , Repeaters ,firewall etc ) Overview
  • TCP/IP overview
  • IP addressing, Sub-netting, super-netting
  • IPv6
  • Planning and Implementing
  • Architecture of Internet and intranet
  • Port Security
  • Spanning tree Protocol
  • Troubleshooting

  • Security Fundamentals
  • Firewalls
  • Define The Type Of Firewalls
  • Security Fundamentals
  • Packet Filtering Firewalls
  • Hybrids
  • Intrusion Detection And Prevention
  • Intrusion risks
  • Security policy
  • Monitoring traffic and open ports
  • Detecting modified files
  • Investigating and verifying detected intrusions
  • Recovering from, reporting and documenting intrusions
  • Define the Types of intrusion Prevention Systems
  • Setup an IPS
  • Manage an IPS
  • Understand Intrusion Prevention
  • Issues with Intrusion Prevention
  • IP Signature and Analysis
  • Risk Analysis
  • Virtual Private Networks
  • Define Virtual Private Networks
  • Deploy User VPNs
  • Benefits of user VPNs
  • Managing User VPNs
  • Issues with User VPNs
  • Deploy Site VPNs
  • Benefits of Site VPNs
  • Managing Site VPNs
  • Issues with Site VPNs

  • Introduction to ITIL
  • Service Strategy
  • Service Design
  • Service Transition
  • Service Operation
  • Continual Service Improvement
  • Data Centre Management
  • Introduction to DCM
  • Data Centre design
  • Best Practices in IT
  • Server Security
  • Storage area network

Introduction to communication, Barriers to communication, Kind of communication, Confidence building Non-verbal Communication, Fluency and vocabulary, Synonyms, Antonyms, Grammar, Noun Pronoun, Verb, Adjective, Preposition, Conjunction, Words of Idioms & phrases, Sentence Construction, Fill up the blanks, Pronunciation, Conversation practice, Polite Conversation, Greeting, Logical reasoning, General Aptitude, Writing: Covering letter, Resume, Email, Presentation Skill, group discussion, Interview skills, Mock interview

3.   Certificate Course in BigData Technologies


Module Details

Linux History and Operation, Installing and Configuring Linux, Shells, Commands, and Navigation, Common Text Editors, Administering a Linux Printer Queue, Introduction to Users and Groups, Linux kernel , The Ext2 Filesystem, Linux shell scripting

Introduction to Python, Basic Syntax, Data Types, Variables, Operators, Input/output, Flow of Control (Modules, Branching), If, If- else, Nested if-else, Looping, For, While, Nested loops, Control Structure, Break, Continue, Pass, Strings and Tuples, Accessing Strings, Basic Operations, String slices, Working with Lists, Introduction, Accessing list, Operations, Function and Methods, Files, Modules, Dictionaries, Functions and Functional Programming, Declaring and calling Functions, Declare, assign and retrieve values from Lists, Introducing Tuples, Accessing tuples

Database Concepts (File System and DBMS), Database Storage Structures (Tablespace, Control files, Data files), Structured and Unstructured data, SQL Commands (DDL, DML & DCL), Dataware Housing concept and tools (ETL tools), No-SQL, Data Models - XML, working with MongoDB),

Introduction to Big Data-  Big data definition, enterprise / structured data, social / unstructured data, unstructured data needs for analytics, What is Big Data, Big Deal about Big Data, Big Data Sources, Industries using Big Data, Big Data challenges.

Hadoop:   Introduction of Big data programming-Hadoop, History of Hadoop, The ecosystem and stack, The Hadoop Distributed File System (HDFS), Components of Hadoop, Design of HDFS, Java interfaces to HDFS, Architecture overview, Development Environment, Hadoop distribution and basic commands, Eclipse development, The HDFS command line and web interfaces, The HDFS Java API (lab), Analyzing the Data with Hadoop, Scaling Out, Hadoop event stream processing, complex event processing, MapReduce Introduction, Developing a Map Reduce Application, How Map Reduce Works, The MapReduce Anatomy of a Map Reduce Job run, Failures, Job Scheduling, Shuffle and Sort, Task execution, Map Reduce Types and Formats, Map Reduce Features, Real-World MapReduce,

Introduction to Pig and HIVE- Programming Pig:   Engine for executing data flows in parallel on Hadoop, Programming with Hive: Data warehouse system for Hadoop, Optimizing with Combiners and Partitioners (lab), More common algorithms: sorting, indexing and searching (lab), Relational manipulation: map-side and reduce-side joins (lab), evolution, purpose and use, HDFS – Overview and concepts, data flow (read and write), interface to HDFS (HTTP, CLI and Java API), high availability and Name Node federation, Map Reduce developing and deploying programs, optimization techniques, Map Reduce Anatomy, Data flow framework programming Map Reduce best practices and debugging, Introduction to Hadoop ecosystem, integration R with Hadoop

Introduction to communication, Barriers to communication, Kind of communication, Confidence building Non-verbal Communication, Fluency and vocabulary, Synonyms, Antonyms, Grammar, Noun Pronoun, Verb, Adjective, Preposition, Conjunction, Words of Idioms & phrases, Sentence Construction, Fill up the blanks, Pronunciation, Conversation practice, Polite Conversation, Greeting, Logical reasoning, General Aptitude, Writing: Covering letter, Resume, Email, Presentation Skill, group discussion, Interview skills, Mock interview.

4.    Certificate Course in Cyber Forensics & Cyber laws


Module Details

Eligibility: Any Engineering /Science graduate with mathematics up to 10+2 level

Course Prerequisite: Candidate should have basic knowledge of computer and networking fundamentals with logical approach and knowledge of Cyber Crimes.

Course Focus: The objective of this course is to provide skills to those students who want to make carrier in Cyber Forensic.

  • Basic Computer Terminology
  • Internet
  • Networking
  • Computer Storage
  • Cell Phone / Mobile Forensics
  • Computer Ethics and Application Programs
  • Cyber Forensic Basics- Introduction to Cyber Forensics
  • Storage Fundamentals
  • File System Concepts
  • Data Recovery
  • Operating System Software and Basic Terminology
  • Introduction to Cyber Security
  • Implementing Hardware Based Security
  • Software Based Firewalls
  • Security Standards
  • Assessing Threat Levels
  • Operating System Attacks
  • Application Attacks
  • Reverse Engineering & Cracking Techniques and Financial Frauds

  • Introduction to Deleted File Recovery
  • Formatted Partition Recovery
  • Data Recovery Tools
  • Data Recovery Procedures and Ethics
  • Preserve and safely handle original media
  • Document a "Chain of Custody"
  • Complete time line analysis of computer files based on file creation
  • File modification and file access
  • Recover Internet Usage Data
  • Recover Swap Files/Temporary Files/Cache Files
  • Introduction to Encase Forensic Edition
  • Forensic Tool Kit (FTK)
  • Use computer forensics software tools to cross validate findings in computer evidence
  • Introduction to Cyber Forensic Investigation
  • Investigation Tools
  • Digital Evidence Collection
  • Evidence Preservation
  • E-Mail Investigation
  • E-Mail Tracking
  • IP Tracking
  • E-Mail Recovery
  • Encryption and Decryption methods
  • Search and Seizure of Computers
  • Recovering deleted evidences
  • Password Cracking
  • Case studies

  • Introduction to IT laws & Cyber Crimes
  • Internet, Hacking
  • Cracking
  • Viruses
  • Virus Attacks
  • Pornography
  • Software Piracy
  • Intellectual property
  • Legal System of Information Technology
  • Social Engineering
  • Understanding Copy Right in Information Technology
  • Understanding the technology of Software software-copyright vs Patent debate
  • Authorship
  • Assignment issues Commissioned work
  • Work for hire Idea/Expression dichotomy
  • Copy right in internet
  • Legal Issues in internet and Software Copyright Jurisdiction Issues
  • Copyright Infringe Remedies of Infringement Multimedia
  • Copyright issues Software Piracy
  • Patents understanding
  • Cyber Crimes
  • Understanding Cyber Crimes in context of Internet
  • Indian Penal Law & Cyber Crimes Fraud Hacking Mischief
  • International law
  • Obscenity and Pornography Internet
  • Potential of Obscenity Indian Law On Obscenity & Pornography Technical
  • Legal solutions International efforts Changes in Indian Laws
  • E-Commerce & Taxation
  • E-Commerce-Salient Features On-Line contracts Mail Box rule Privities of
  • Contracts Jurisdiction issues in E-Commerce Electronic Data Interchange
  • Security and Evidence in E-Commerce Dual Key encryption Digital signatures security issues
  • UNCITRAL model law of E-Commerce
  • Indian Legal Position on E-Commerce IT Act 2000/Indian Evidence Act/Draft law on E-Commerce

Introduction to communication, Barriers to communication, Kind of communication, Confidence building Non-verbal Communication, Fluency and vocabulary, Synonyms, Antonyms, Grammar, Noun Pronoun, Verb, Adjective, Preposition, Conjunction, Words of Idioms & phrases, Sentence Construction, Fill up the blanks, Pronunciation, Conversation practice, Polite Conversation, Greeting, Logical reasoning, General Aptitude, Writing: Covering letter, Resume, Email, Presentation Skill, group discussion, Interview skills, Mock interview

5.   Certificate Course in BigData Analytics (CCBDA)


Module Details

Big Data - Beyond the Hype, Big Data Skills and Sources of Big Data, Big Data Adoption, What is Big Data?, Characteristics of Big Data - The Four V's, Understanding Big Data with Examples, The Big Data Platform, Technical Details of Big Data Components, Text Analytics and Streams, Cloud and Big Data

Probability & Statistics:  Introduction to Statistics- Descriptive Statistics, Summary Statistics Basic probability theory, Statistical Concepts (uni-variate and bi-variate sampling, distributions, re-sampling, statistical Inference, prediction error), Probability Distribution (Continuous and discrete- Normal, Bernoulli, Binomial, Negative Binomial, Geometric and Poisson distribution) , Bayes’ Theorem, Central Limit theorem, Data Exploration & preparation, Concepts of Correlation, Regression, Covariance, Outliers etc.

Programming: Introduction & Installation of R, R Basics, Finding Help, Code Editors for R, Command Packages, Manipulating and Processing Data in R, Reading and Getting Data into R, Exporting Data from R, Data Objects-Data Types & Data Structure. Viewing Named Objects, Structure of Data Items, Manipulating and Processing Data in R (Creating, Accessing , Sorting data frames, Extracting, Combining, Merging, reshaping data frames), Control Structures, Functions in R (numeric, character, statistical), working with objects, Viewing Objects within Objects, Constructing Data Objects, Building R Packages, Running and Manipulating Packages, Non parametric Tests- ANOVA, chi-Square, t-Test, U-Test, Introduction to Graphical Analysis, Using Plots(Box Plots, Scatter plot, Pie Charts, Bar charts, Line Chart), Plotting variables, Designing Special Plots, Simple Liner Regression, Multiple Regression

Information Visualization, Data analytics Life Cycle, Analytic Processes and Tools, Analysis vs. Reporting, Modern Data Analytic Tools, Visualization Techniques, Visual Encodings, Visualization algorithms, Data collection and binding, Cognitive issues, Interactive visualization, Visualizing big data – structured vs unstructured, Visual Analytics, Geomapping, Dashboard Design

Introduction to Business Analytics using some case studies, Making Right Business Decisions based on data, Exploratory Data Analysis - Visualization and Exploring Data, Descriptive Statistical Measures, Probability Distribution and Data, Sampling and Estimation, Statistical Interfaces, Predictive modeling and analysis, Regression Analysis, Forecasting Techniques, Simulation and Risk Analysis, Optimization, Linear, Non linear, Integer, Decision Analysis, Strategy and Analytics Overview of Factor Analysis, Directional Data Analytics, Functional Data Analysis

Introduction to communication, Barriers to communication, Kind of communication, Confidence building Non-verbal Communication, Fluency and vocabulary, Synonyms, Antonyms, Grammar, Noun Pronoun, Verb, Adjective, Preposition, Conjunction, Words of Idioms & phrases, Sentence Construction, Fill up the blanks, Pronunciation, Conversation practice, Polite Conversation, Greeting, Logical reasoning, General Aptitude, Writing: Covering letter, Resume, Email, Presentation Skill, group discussion, Interview skills, Mock interview.

6.   Certificate Course in HPC Application Development (CCHPCAD)


Module Details

Eligibility: Any Engineering /Science graduate with mathematics up to 10+2 level.

Course Pre-requisites:  Sound knowledge of Computing Fundamentals and Fundamentals of Programming and Java Programming.

Course Focus:  The objective of this course is to provide the student with hands on experience in Application development for HPC.

Why OpenMP , OpenMP Programming Model, OpenMP constructs, Case-Studies (Algorithms and Parallelization Approaches), Matrix –Matrix-multiplication. OpenMP4.0

Basic MPI, MPI Point – to Point, MPI Collective Communication: Data Synchronization, Data Movement, Collective Computation . Advance MPI: Derived Data Types, Derived Types, Special type Constructors, Type Matching, Packing/Unpacking Data, Groups and Communicators: Virtual Topologies, MPI3 Standard, MPI Threads, Case Studies (Algorithms and Parallelization Approaches)

Introduction to GPGPU, GPU Performance Vs CPU Performance, GPU Computing Application Domain, nVIDIA’s GPGPU Hardware Model,GPU Computing with CUDA , Thread Hierarchy, Memory Hierarchy, CUDA constructs, Case-Studies (Algorithms and Parallelization Approaches): Matrix – Multiplication

Intel Many Core Processor Programming :  Basic of Many Integrated Core (MIC) architecture , Programming models of MIC : Native mode, offload, Symmetric , Porting of HPC applications on MIC , Tuning and optimization of HPC appli cations on MIC architecture, vectorizations and optimization.

Profiling and Debugging of codes tools: gprof, Vtune, gdb, Performance library like mkl, lapack, fft , Analysis tools like : ITAC , MPI libraries. Demo of the sample code by using the above tools.

Introduction to communication, Barriers to communication, Kind of communication, Confidence building Non-verbal Communication, Fluency and vocabulary, Synonyms, Antonyms, Grammar, Noun Pronoun, Verb, Adjective, Preposition, Conjunction, Words of Idioms & phrases, Sentence Construction, Fill up the blanks, Pronunciation, Conversation practice, Polite Conversation, Greeting, Logical reasoning, General Aptitude, Writing: Covering letter, Resume, Email, Presentation Skill, group discussion, Interview skills, Mock interview.

7.   Certificate Course in HPC environment and Best Practices (CCHPCE)


Module Details

Eligibility:  Any Engineering /Science graduate with mathematics up to 10+2 level

Course Pre-requisites: Sound knowledge of Computing Fundamentals and Fundamentals of Programming. 

Course Focus: The objective of this course is to provide the student with an expertise in Technical Support Services who wants to make carrier in HPC domain.

Introduction to Unix, operating systems (kernel vs. userspace, processes/threads, file system semantics), Shell scripting (bourne shell), Advanced portable scripting (e.g. python) Compiler architecture (pre-processor, compiler, assembler, linker) and use Of libraries, Configuring, compiling, linking software packages (including use of make) Source code management (git, mercurial), Basic of Visualization tools, Unit and Regression testing, Software documentation.

Computer architecture, Memory hierarchy, Modern multi core CPU systems, Overview On massively parallel processors, Parallel, architectures for HPC and further trends, Basic Principle of storage, Debugging and profiling of a serial applications, False sharing and Memory efficiency on Multi core systems, Practical introduction to software optimization.

Introduction to parallel computing, Principles of parallel algorithm design and multilevel parallelism, Message Passing parallelization (MPI), Shared memory parallelization (OpenMP), Analysis of scalability and parallel performance metrics, Overview To the debugging and the profiling of parallel applications, Introduction to the Programming of massively parallel processors, OpenCL, Practical introduction to parallel Math libraries , Further trends of parallel programming in HPC.

HPC system deployment, Software Provisioning, Managing hardware Diversity, Scheduling and resource management, Usage accounting Data management (quotas, purging, archival), Sustainable HPC Computing

Infrastructure, Green computing, Grid and Cloud Computing, Debug versus Optimized mode, Multilanguage programming, Strategies for developing Scientific codes, Collaborative ways of developing scientific and technical Packages, Tools for developing large software packages.

From math to computing: Computer representation of numbers, Overflow, underflow, catastrophic cancellation, Stability, Conditioning, Direct translation of symbols to code is dangerous, The purpose of computing is insight not numbers, The foundations of numerical analysis, Polynomial Interpolation, Numerical Integration, Resolution of non—linear systems, Resolution of large linear systems, Eigen values, Approximation Numerical Solution of ODEs , Numerical solution of PDEs, Algorithmic efficiency and big O notation, Examples from classic data structures and algorithms

Numerical linear algebra, Simultaneous linear equations, Column space, row space and rank, Rank, basis, span, Norms and distance, Trace and determinant, Eigenvalues and eigenvectors, Inner product, Outer product, Einstein summation notation, Matrices as linear transforms, Types of matrices, Square and non-square, Singular, Positive definite
Idempotent and projections, Orthogonal and orthonormal, Symmetric Transition, Matrix geometry illustrated, Examples of computation in statistics, Estimating parameters (point and interval estimates), Estimating functions, Feature extraction, class discovery and dimension reduction, Classification and regression, Simulations and computational inference

Introduction to communication, Barriers to communication, Kind of communication Confidence building Non-verbal Communication, Fluency and vocabulary, Synonyms,Antonyms, Grammar, Noun Pronoun, Verb, Adjective, Preposition, Conjunction, Wordsof Idioms & phrases, Sentence Construction, Fill up the blanks, Pronunciation, Conversation practice, Polite Conversation, Greeting, Logical reasoning, General Aptitude, Writing: Covering letter, Resume, Email, Presentation Skill, group discussion, Interview skills, Mock interview.