Data Analytics | Full Stack Development | AWS Cloud Computing | Data Science Machine Learning | Cyber Security
About IITP 2023
During the Internship cum Training Program students get familiar with the work culture of the companies and get the chance to work on real-time case study projects. The students mainly learn the practical implementation of industrial Technologies i.e. Artificial Intelligence Machine Learning Data Science and IoT these may involve the task of coding, configuration, design, programming, installation and basic electronics etc under experienced industrial experts and mentors.
fall in love with program's features
1. More than 80% hand on Session
3. Discussion forum
5. Free Access to Digital learning Resources
2. Projects oriented learning
4. Registered on AICTE Internship Portal
6. Globally Recognized Internship Certificate
ELIGIBILITY & REGISTRATION PROCEDURE
- Any under-graduating candidate can join the program.
- Candidate has to pay INR 500/- as a registration fee, this fee will include in the original fee.
- Remaining fee the candidate can pay on 1st day of Training cum Internship
- After Completion of registration company will book your seats for particular Internship cum Training
CURRICULUM, DURATION, AND FEE
Cloud Computing (AWS)
Cloud Computing using AWS training and internship is a program that teaches engineering students how to design, deploy, and manage applications and services in the cloud using Amazon Web Services (AWS). The program covers the basics of cloud computing, AWS architecture, and services such as EC2, S3, Lambda, and DynamoDB.
During the training, students will learn how to use AWS to build and deploy applications, manage resources, monitor performance, and troubleshoot issues. The program also focuses on teaching students how to optimize costs and improve security in cloud computing environments.
The program’s internship component allows students to apply the skills they have learned to real-world projects and gain practical experience in cloud computing using AWS. This can be a valuable experience for students interested in pursuing careers in cloud computing, DevOps, or related fields.
Overall, the Cloud Computing using AWS training and internship program is an excellent opportunity for engineering students to develop essential skills in cloud computing and gain practical experience in a rapidly growing field.
Key Ponts:
- Attendee: Any UG Students
- Duration: 15/30 Days (Monday to Saturday)
- Pay only 2500/- out of 6999/- (Pay 500 During registration + 2000 1st day of Session)
- Starting Batch: 06th July 2023
- Pre-requisites: Basic understanding of Linux
- Certificate: Each Candidate will get a certificate of Internship
- Mode: Online Live session on Microsoft Team
- Lifetime access to the recording of live sessions, and other learning materials
Curriculum
- Introduction to cloud computing
- Essential Characteristics of Cloud Computing
- Service Models in Cloud computing
- Deployment models in Cloud Computing
- Introduction to AWS
- AWS Account creation &free tier limitations overview
- Basics of Linux for AWS
- Linux Installation and Basic commands overview
- Web Server and Services Configurations
- Compute
- EC2 Instance Launch Wizard
- EC2 Instance Types
- Generating custom Public Key and Private keys for EC2 instances
- Security groups
- Volumes and Snapshots
- Creating customized Amazon Machine Images
- RAID Overview and RAID Configurations
- User Data and Metadata
- ElasticLoad Balancers & Health Checks
- Auto Scaling Groups
- CloudWatch
- Creating Billing Alarm and EC2 instance alarms.
- AWS CLI&EC2 Roles
- Elastic File System
- AWS Lightsail
- Elastic Beanstalk
- Placement Groups
- Amazon CloudWatch Alarms
- AWS CloudTrail Logs
- Amazon S3 Access Logs
- AWS Trusted Advisor
- Logging configuration of Amazon S3 buckets.
- Security checks for Amazon S3 buckets that have open access permissions.
- Fault tolerance checks for Amazon S3 buckets that don’t have versioning enabled, or have versioning suspended.
- Step 1: Enable provisioning in AWS SSO
- Step 2: Configure provisioning in Okta
- Step 3: Assign access for users and groups in Okta
- (Optional) Step 4: Configure user attributes in Okta for access control in AWS SSO
- (Optional) Passing attributes for access control
- Troubleshooting
- DNS Records overview
- Routing Policies
- Hosting sample Website and configuring Policies
- Simple Routing Policy
- Latency Routing Policy
- Failover Routing Policy
- Weighted Routing Policy
- Geolocation Routing Policy.
- Launching a RDS Instances (MySQL, MSSQL & Aurora)
- Multi-AZ & Read Replicas for RDS instances
- DynamoDB
- Redshift
- Elastichache
- Database Migration Service and Schema conversion tool
- Networking Basics
- Creating custom VPCs and custom Subnets
- Network ACL’s
- Route Tables & IGW
- VPC Peering
- Flow log creation
- VPN Configuration with AWS (OpenVPN)
- Simple Email Service
- Simple Queue Service
- Simple Workflow Service
- Simple Notification Service
- SMS – Server Migration Service
- Migrating server from on-premises to cloud
- Cloud Formation
- Directory Services and Adding EC2 instance to Domain
- AWS TCO Calculator and Simple Monthly calculator
Working Final Project
Splitting final Project into phases Working on structuring porject
Do’s and Don’ts with Machine Learning Productization of Machine Learning
Application
Data Analytics using python
Data Analytics using Python training and internship is a program that teaches engineering students how to use the Python programming language to analyze large datasets and derive insights from them. The program covers Python programming basics, data manipulation using Python libraries such as Pandas, data visualization using libraries such as Matplotlib and Seaborn, and statistical analysis.
During the training, students will learn how to load and clean data, apply statistical methods to analyze data, and visualize data using different techniques. The program also focuses on teaching students how to communicate their findings effectively using data visualization and storytelling techniques.
The program’s internship component allows students to apply the skills they have learned to real-world projects and gain practical experience in data analytics. This can be a valuable experience for students interested in pursuing careers in data science or related fields.
Overall, the Data Analytics using Python training and internship program is an excellent opportunity for engineering students to develop essential skills in data analytics and gain practical experience in a rapidly growing field.
Key Ponts:
- Attendee: Any UG/PG Students
- Duration: 15/30 Days (Monday to Saturday)
- Pay only 2000/- out of 5999/- (Registration fee INR 500 During registration + 1500 1st day of Session)
- Starting Batches: 26th June 2023, 7 PM onwards
- Certificate: The candidate will get a certificate of Internship
- Mode: Online Live session on Microsoft Team/Zoom
- Lifetime access to the recording of live sessions, and other learning materials
Curriculum
- Getting started with Python
- What is Python?
- Installing Anaconda
- Variables, and Data Structure
- List, tuples and dictionary
- Control Structure
- Functions in python
- Lambda functions
- Object Oriented Programming Modules
- Using Packages Os package, time and datetime
- File Handling in Python
- Miscellaneous Functions in python
- Introduction to Statistics
- Population and Sample
- Descriptive Statistics v/s Inferential Statistics
- Types of variable
- Categorical and Continuous Data
- Ratio and Interval
- Nominal and Ordinal Data
- Descriptive Statistics
- Measure of Central Tendency – Mean, Mode and Median
- Percentile and Quartile
- Measure of Spread – IQR, Variance and Standard Deviation
- Coefficient of Variation
- Measure of Shape – Kurtosis and Skewness
- Correlation Analysis
- Inferential Statistics
- Empirical Rule & Chebyshev’s Theorem
- Z Test
- One Sample T test, independent t test
- ANOVA – f test
- Chi Square test
- Working with Numpy
- NumPy Overview
- Properties, Purpose, and Types of ndarray
- Class and Attributes of ndarray Object
- Basic Operations: Concept and Examples
- Accessing Array
- Elements: Indexing, Slicing, Iteration, Indexing with Boolean Arrays
- Shape Manipulation & Broadcasting
- Linear Algebra using numpy
- Stacking and resizing the array
- random numbers using numpy
- Working with Pandas
- Data Structures
- Series, DataFrame & Panel
- DataFrame basic properties
- Importing excel sheets, csv files, executing sql queries
- Importing and exporting json files
- Data Selection and Filtering
- Selection of columns and rows
- Filtering Dataframes
- Filtering – AND operaton and OR operation
- Working with Pandas
- Data Cleaning
- Handling Duplicates
- Handling unusual values
- Handling missing values
- Finding unique values
- Descriptive Analysis with pandas
- Creating new features
- Creating new categorical features from continuous variable
- Combining multiple dataframes
- groupby operations
- groupby statistical Analysis
- Apply method
- String Manipulation
- Basic Visualization with matplotlib
- Matplotlib Features
- Line Properties
- Plot with (x, y)
- Controlling Line Patterns and Colors
- Set Axis, Labels, and Legend Properties
- Alpha and Annotation
- Multiple PlotsSubplots
- Advance visualization using seaborn
- Types of Plots and Seaborn
- Boxplots
- Distribution Plots
- Countplots
- Heatmaps
- Voilin plots
- Swarmplots and pointplots
- Data Science Standard Project
- Data Science Project Life cycle
- Project Topic
- Data Capturing
- Data Cleaning
- Data Analytics
- Working on tools
- Data Visualization tools
- Project Report Completion
FULL STACK DEVELOPMENT
Full Stack Web Developer course online will enable you to build interactive and responsive web applications using both front-end and back-end technologies. Full Stack Developer course syllabus starts with basics of Web Development, covers JavaScript and jQuery essentials, guides you to build remarkable user interface via Angular or React, helps you to build scalable backend applications using Express & Node.js plus manage data using MongoDB.
Key Ponts:
- Attendee: Any UG Students
- Duration: 15/30 Days (Monday to Saturday)
- Pay only 2000/- out of 6999/- (Pay 1000 During registration + 1500 1st day of Session)
- Starting Batches: NA
- Certificate: Each Candidate will get a certificate of Internship
- Mode: Online Live session on Microsoft Team
- Lifetime access to the recording of live sessions, and other learning materials
Curriculum
- Understanding web apps
- Usage of web apps
- Domain and Hosting
- Security and storage
- Technologies for
- Web Application development
- Examples of Web Apps
- Fundamentals of UI/UX
- What is UI/UX?
- UI Developer roles and Responsibilities
- UX Process
- Wireframes and prototypes
- Current market requirements on UI and UX
- User mindset, journey, expectations, mental models
- UI Design tools and Principles
- UI, UX best practices
- Database Fundamentals
Introduction to Databases and their applications
Types of databases
Understanding DBMS
Relational and Non-relational Databases
Database technologies and their uses
Understanding distributed storage and data lake
Applications of data lake
MySQL tool installation
MySQL Workbench Introduction
SQL Introduction
Creating databases, tables
SQL standard queries: Insert, select, update - Working with SQL
SQL standard queries
SQL data filtering
Basic data exploration with SQL
SQL data management - NoSQL databases
Concept of NoSQL?
Why NoSQL
Compare NoSQL, and RDBMS
Types of NoSQL Database
Key-Value Stores
MongoDB Module
Features of MongoDB Module
Principles & Design Goals for MongoDB Server and Database
MongoDB tools
MongoDB Installation on Windows and cloud
CRUD operations
Basic MongoDB Commands
Read and Query Operations
Concepts of Modelling Database
Modelling Relationship
- HTML Introduction
HTML and its design principles
HTML tags, elements, and formatting
HTML Design approach
HTML Lists, tables, forms, attributes, triggers
HTML iframes, embedding (audio, video, drag & Drop)
Autogenerating HTML script
HTML5 best practices
HTML5 Local storage
HTML5 canvas
CSS & Bootstrap - CSS
CSS Semantics and selectors
CSS Styling(Color, Backgrounds, Height width)
CSS Box Model
Tables, buttons
Form Validation
CSS Float & Clear
Selectors & Display CSS
CSS Align Horizontal & Center Responsive Web Design
View Port, Grid View, media Queries and flex box
CSS Animation
- JavaScript
Introduction of Javascript
JavaScript use cases
Syntax, operations, variables, control flow
JS functions, loops, arrays, and operations
JS for validation
JavaScript with HTML Attributes
JavaScript HTML DOM Elements
JavaScript with CSS - ReactJS
Introduction to React
Features of React
Setting up React and working with react
Render HTML in React
Lists, keys, forms, web services
Composition vs Inheritance
Thinking In React
Accessibility
Code-Splitting
Context
React JSX
Adding Forms in React
React Router
Styling React Using CSS
React Hooks
Integrating with Other Libraries
- Node.js – Introduction, use cases and applications
Environment Setup
REPL Terminal
Package Manager (NPM)
MVC Architecture for Node.js
Basic syntaxing, writing logics and callbacks concept
Event Loop & Event Emitter
Event Emitter
Buffers
Streams
File System
Global Objects
Utility Modules
Web Module
Express Framework
Working Final Project
Splitting final Project into phases Working on structuring porject
Do’s and Don’ts with Machine Learning Productization of Machine Learning
Application
DATA SCINECE & MACHINE LEARNING
Data Science and Machine Learning Training and internship is a program that teaches engineering students how to apply machine learning techniques to solve real-world problems using data. The program covers the basics of data science, statistics, machine learning algorithms, and practical aspects of data preprocessing, feature engineering, and model selection.
During the training, students will learn how to clean and preprocess data, engineer features, select appropriate models, and evaluate their performance. The program also focuses on teaching students how to communicate their findings effectively and interpret the results.
The internship component of the program allows students to apply the skills they have learned to real-world projects and gain practical experience in data science and machine learning. This can be a valuable experience for students interested in pursuing careers in data science, machine learning, or related fields.
Overall, the Data Science and Machine Learning training and internship program is an excellent opportunity for engineering students to develop essential data science and machine learning skills and gain practical experience in a rapidly growing field.
Key Ponts:
- Attendee: Any UG Students
- Duration: 15/30 Days (Monday to Saturday)
- Pay only 3500/- out of 6999/- (Pay 1000 During registration + 2500 1st day of Session)
- Starting Batches: NA
- Prerequisites: Python Programming and Statistics
- Certificate: Each Candidate will get a certificate of Internship
- Mode: Online Live session on Microsoft Team
- Lifetime access to the recording of live sessions, and other learning materials
Table of Content:
- Module 1: Statistical Analysis
- Module 2: Hypothesis Testing
- Module 3: Probabilistic Analysis
- Module 4: Python Programming
- Project: 1 Selection of Project
- Module 5: Data Import/Export and Data Manipulation
- Module 6: Predictive Analysis
- Module 7: Regression and Classification
- Module 8: Time Series Forecasting
- Module 9: Anomaly Detection
- Project 2 and final report submission.
This link will take you to the RAZORPAY page where you may fill out the form and pay INR 1000.
artificial intelligence and deep learning(advanced)
In this program, students will learn how to build and deploy intelligent systems using deep learning techniques. The program covers the basics of artificial intelligence, deep learning algorithms, and their applications in image processing, natural language processing, and other domains.
During the training, students will learn how to use popular deep learning frameworks such as TensorFlow and PyTorch, preprocess data, build deep learning models, and optimize their performance. The program also focuses on teaching students how to interpret and communicate the results of their models effectively.
The internship component of the program allows students to apply the skills they have learned to real-world projects and gain practical experience in artificial intelligence and deep learning. This can be a valuable experience for students interested in pursuing careers in artificial intelligence, machine learning, or related fields.
Overall, the Artificial Intelligence and Deep Learning training and internship program is an excellent opportunity for engineering students to develop essential skills in artificial intelligence and deep learning and gain practical experience in a rapidly growing field.
Key Ponts:
- Attendee: Any UG/PG Students
- Duration: 30 Days (Monday to Saturday)
- Pay only 4999/- out of 9999/- ( Pay 1000 During registration + 3999 1st day of Session)
- Starting Batches: NA
- Pre-requisites: Machine Learning Techniques
- Certificate: Each Candidate will get a certificate of Internship
- Mode: Online Live session on Microsoft Team
- Lifetime access to the recording of live sessions, and other learning materials
Table of Content:
- Module 1: Introduction to AI
- Module 2: Python Programming
- Module 3: Statistics for ML
- Module 4: Python for AI & ML
- Project -1
- Module 5: ML- Linear Regression
- Module 6: ML- Logistic Regression
- Module 7: ML- KNN & Decision Tree
- Module 8: ML- SVM & Ensemble Learning
- Module 9: DL- Artificial Neural Networks
- Module 10: DL- Unsupervised Learning
- Module 11: Natural Language Processing
- Project 2 and final project submission.
This link will take you to the RAZORPAY page where you may fill out the form and pay INR 1000.
do not miss once in life time opportunity
Limited Seats Available, Reserve your Seat Now
FAQ'S
Candidate will get a Certificate of training if you attend the training only, Candidate has to submit the project report to get the certificate of Internship, the attendee can get only one certificate.
Yes, we are registered on Internship.aicte-india.org the IITP certificate is valid all over the globe.
IITP is available only Online and On-Campus
Any UG/PG students can attend the program.
Yes, it’s given in the content section, we charge a very minimum fee to cover our Technical and Management expenses.
You can book your seat by paying INR 1000/- as a registration fee. The remaining fee you can pay on 1st day of the program, the registration fee will include in your total fee for more details please check the content section of each topic
Skill-Based Pre-requisites: please check the content section of each domain.
Resource-Based requisites: Candidate must have a laptop/Computer, and Internet facility for 2 hours daily.
No, You need NOT visit the company office for any registration or documentation, Program is totally online.
College ID required/ Bonafide /Letter of Internship
