AI Full Stack Course

Be the AI Full Stack Professional Learning Front End, Middleware, Backend, and AI Technologies

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Languages and Tools covered

Essentials & Web Technologies

This module provides a foundational understanding of web development technologies and programming fundamentals, focusing on the essentials of programming, front-end technologies, and version control systems. Students will learn to build and manage basic web applications using HTML, CSS, and JavaScript while gaining familiarity with Linux and Git.

Fundamentals of Programming

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  • Introduction to Programming Concepts
  • Variables and Data Types
  • Control Structures (Loops, Conditionals)
  • Functions and Modular Programming

HTML & CSS

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  • HTML Basics: Structure, Elements, and Attributes
  • CSS Basics: Selectors, Properties, and Styling
  • Responsive Web Design with Flexbox and Grid
  • Introduction to Web Accessibility

Linux

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  • Introduction to Linux Operating System
  • Basic Linux Commands and File System Navigation
  • User and Permission Management
  • Shell Scripting Basics

Git & GitHub

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  • Version Control Systems: Git Overview
  • Basic Git Commands: Cloning, Committing, Pushing
  • Branching and Merging
  • Collaborating on GitHub: Pull Requests and Issues

JavaScript and TypeScript

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  • JavaScript Basics: Syntax, Variables, and Functions
  • DOM Manipulation and Event Handling
  • Introduction to ES6+ Features
  • Getting Started with TypeScript: Types and Interfaces

JavaScript Framework

This module introduces students to modern JavaScript frameworks used for building interactive web applications. Students will choose between React JS or Angular to develop dynamic front-end interfaces that can integrate with AI-powered backends.

React JS

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  • Introduction to React and Component Architecture
  • State Management and Props
  • React Hooks: useState, useEffect
  • Routing with React Router
  • Introduction to Redux for State Management
  • Integrating AI APIs in React Applications

Angular

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  • Introduction to Angular and MVC Architecture
  • Components, Templates, and Data Binding
  • Services and Dependency Injection
  • Routing and Navigation in Angular
  • State Management with NgRx
  • AI Service Integration in Angular

AI & Machine Learning Fundamentals

This module introduces the core concepts of artificial intelligence and machine learning, focusing on Python programming for AI, data preprocessing, model development, and evaluation. Students will learn to build and train machine learning models using popular frameworks.

Python for AI/ML

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  • Python Basics for Data Science
  • NumPy and Pandas for Data Manipulation
  • Data Visualization with Matplotlib and Seaborn
  • Working with APIs and Data Sources

Machine Learning Basics

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  • Introduction to Machine Learning Concepts
  • Supervised Learning: Regression and Classification
  • Unsupervised Learning: Clustering
  • Model Evaluation and Validation
  • Feature Engineering and Selection

Deep Learning with TensorFlow & Keras

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  • Introduction to Neural Networks
  • Building Deep Learning Models with TensorFlow
  • Keras API for Model Development
  • Convolutional Neural Networks (CNNs)
  • Recurrent Neural Networks (RNNs)
  • Transfer Learning and Pre-trained Models

Computer Vision with OpenCV

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  • Introduction to Computer Vision
  • Image Processing with OpenCV
  • Object Detection and Recognition
  • Image Classification Models

Natural Language Processing

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  • Text Preprocessing and Tokenization
  • Sentiment Analysis
  • Text Classification
  • Introduction to Transformers and LLMs

Project Deployment

This module covers the essentials of deploying web applications and AI models, focusing on virtual machines, deployment tools, and cloud services. Students will learn how to deploy their projects using Linux and cloud platforms, manage load balancing, and configure firewalls.

Essentials of Deployment

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  • Introduction to Deployment: Concepts and Strategies
  • Setting Up a Development Environment
  • CI/CD Pipelines
  • Containerization with Docker

Virtual Machines

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  • Introduction to Virtualization and Virtual Machines
  • Setting Up Virtual Machines with VMware/VirtualBox
  • Deploying Web Applications on Virtual Machines

Cloud Deployment (AWS/Azure)

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  • Deploying Applications on Cloud Platforms
  • AI Model Deployment on Cloud
  • Serverless Architecture for AI Applications
  • Managing Cloud Resources

Load Balancing & Firewall Configuration

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  • Understanding Load Balancing and Its Importance
  • Setting Up Load Balancers (HAProxy, NGINX)
  • Configuring Firewalls for Web Security

Database

This module introduces the core concepts of databases, focusing on both relational and non-relational databases. Students will learn how to design, query, and manage databases using MySQL and MongoDB, with special focus on storing and retrieving data for AI applications.

MySQL (RDBMS)

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  • Introduction to Relational Databases
  • Designing Database Schemas
  • SQL Basics: SELECT, INSERT, UPDATE, DELETE
  • Joins, Indexes, and Query Optimization
  • Database Backup and Recovery

MongoDB

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  • Introduction to NoSQL and MongoDB
  • Document-Oriented Database Concepts
  • CRUD Operations in MongoDB
  • Indexing and Aggregation
  • Data Modeling and Schema Design
  • Storing AI Model Data and Predictions

Backend Development with AI Integration

This module covers the development of server-side applications with AI integration, focusing on RESTful API design, server-side scripting with Node.js, and integrating AI models into backend services. Students will learn to build scalable backend services that can serve AI predictions and manage AI workflows.

REST API

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  • Introduction to RESTful Web Services
  • Designing and Implementing REST APIs
  • Authentication and Authorization
  • API Testing with Postman
  • Versioning and Documentation of APIs
  • AI Model API Endpoints

Node.js with AI Integration

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  • Introduction to Node.js and Asynchronous Programming
  • Building RESTful APIs with Express.js
  • Connecting to Databases (MySQL/MongoDB) with Node.js
  • Error Handling and Middleware
  • Integrating Python AI Models with Node.js
  • AI Model Serving and Inference
  • Deploying Node.js Applications with AI

AI Full Stack Projects

Online

₹70,000/ *

(Reach out to us to claim your offer)
  • Online Training Program

Offline

₹75,000/ *

(Reach out to us to claim your offer)
  • Classroom Training Program
  • 28 Weeks, 84 Sessions Program
  • 5 Major Projects with AI Integration & Deployment
  • Hybrid Learning Model
  • Certification Program
  • Internship Included
  • Job Placement Assistance
  • Hackathon with Certification
  • Regular or Weekend Batches

Curriculum

The Curriculum supports step-by-step transformation while building confidence to handle various domain problems.

28 Weeks

Learning content

20+

Languages & Tools

Download Curriculum

WhyAI Full Stack

AI Full Stack professionals are versatile experts skilled in front-end, back-end, and AI/ML technologies, offering complete intelligent application solutions. This course equips you with essential skills in web development, AI model integration, deployment, and database management to become a highly sought-after professional in the AI industry.

Front-End Development:
Learn to build intuitive and responsive user interfaces using the latest front-end technologies, ensuring a seamless user experience for AI-powered applications.
Back-End Development with AI Integration:
Gain expertise in server-side programming to manage databases, servers, and application logic, with special focus on integrating AI models and APIs into your applications.
AI/ML Model Development & Deployment:
Master AI and machine learning model development using TensorFlow, Keras, and scikit-learn, and learn to deploy these models in production environments.
Database Management:
Master database management skills to confidently deploy, debug, and maintain databases for both traditional applications and AI-driven systems.
Data Science

Your Pathway to Mastery

AI Full Stack Development Learning Path

A comprehensive roadmap to becoming job-ready in AI-powered Full Stack Development.

App screenshot
HTML/CSS Pre-Videos
Learn the basics of web development before attending sessions.
Offline / Online Sessions
Choose your preferred mode of learning.
Recorded Sessions
Access recorded sessions for revision or catch-up.
Coding Exercises
Practice coding with hands-on exercises.
Jupyter Notebooks
Work with interactive notebooks for AI and backend programming.
Assignments
Apply your knowledge through practical assignments.
Periodical Assessments
Test your understanding and track your progress.
Projects - Mini & Major
Develop AI-powered full-fledged applications to demonstrate your skills.
Front-end, Back-end & AI Integration
Master client-side, server-side, and AI model integration.
AI Model Deployment
Learn to deploy machine learning models in production environments.
Interview Preparation
Prepare for technical interviews with curated questions and answers.
Final Assessment
Comprehensive assessment to ensure you are job-ready.
Job Readiness
Get ready for the job market with mock interviews, CV preparation, and HR rounds.

Course Information

Become an AI full stack professional to develop cutting-edge intelligent web applications that showcase the skills the market is looking for. This program was designed and developed by industry experts covering the necessary technologies you would need to evolve into an AI-powered full stack professional. This program covers frontend, backend, database, AI/ML model development, and deployment techniques. Post completion of the course you would gain industry-ready skills to be an independent intelligent web application developer. Project-based learning would impart confidence to design, develop, debug, and deploy AI-integrated web applications.

Best AI Full Stack Development Program

The best AI full stack course in Hyderabad? Cedlearn provides comprehensive training in front-end, back-end, and AI/ML technologies including HTML, CSS, JavaScript, Node.js, React, Python, TensorFlow, and more. Learn to build intelligent web applications by integrating AI models, train under industry leaders, and launch your career as an AI-powered full stack professional.

Easy to learn and Job-ready program
Our curriculum is structured to ease you into AI-powered full stack development, ensuring you are job-ready by the end of the program with both web development and AI expertise.
Coding involved
You will get hands-on with coding from day one, covering everything from basic HTML to advanced JavaScript frameworks, backend programming, and AI model integration.
Hybrid Learning Model
Experience a blend of online and offline learning, providing flexible and effective learning opportunities for both web development and AI concepts.
Minimum Batch Size
Enjoy personalized attention with our small batch sizes, ensuring that each student gets the guidance they need for complex AI and full stack concepts.
Job Preparation with Profile building
Get job-ready with expert guidance on resume building, mock interviews, and portfolio development showcasing both web and AI projects.
Internships and AI projects
Gain hands-on experience with internships and real-world AI-powered projects, boosting your practical skills and employability in the AI industry.
Scholarship Assessments
Avail of scholarships by taking assessments designed to help you finance your education and reduce your course fees.

Course Highlights

If you're preparing to enhance your skills and knowledge. Our courses emphasize foundational learning, practical implementation through projects, and real-world experience, ensuring you are well-prepared for the challenges of your chosen field. From engaging hybrid learning sessions to hands-on internships, our comprehensive approach is designed to build your confidence and transform your expertise into career-ready skills.

Prepare

Foundation courses designed to bring you up to the speed, irrespective of your background.

Learn

Hybrid Learning to engage learners even before the class for effective knowledge transfer.

Implement

Project-Based Learning for confidence building and transferring knowledge into skills.

Experience

Internships & Job Readiness to give real-time experience and prepare for interviews.

AI Full Stack Certificate

Job for AI Full Stack

As an AI Full Stack professional, you would be eligible to work on cutting-edge applications that combine web development with artificial intelligence. You could lead teams developing intelligent web applications, integrate AI models into production systems, and work on innovative solutions that leverage both front-end, back-end, and AI technologies. The demand for talented AI Full Stack professionals is growing exponentially as organizations seek to build intelligent, data-driven applications. This role offers excellent career growth and competitive compensation.

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Contact us

Get in Touch With Us

Phone number
8977944952/53
Email
hello@cedlearn.com
DELHI
HYDERABAD
KOCHI
BANGLORE

Business Hours :

Monday - Saturday: 9:00a.m to 8:00p.m

Sunday: With Appointment Only

Send a Message

Write to us. We would catch up with you as soon as we receive your message

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scholarship & discounts

We believe in encouraging talented learners with Scholarships to avoid the learning hurdles due to financial limitations. However scholarships must be awarded based on the merit and hence our assessments. We would be glad to assess learners using our multi-dimensional assessment to identify the dormant potential and thus encourage them through the learning process by offering financial benefits. To know more you could contact us or register for the online assessment. If you are not clear on the career path in the field of AI, please feel free to meet our career counsellor. We would be glad to guide you through the career options to draft a personalized career path.



    • Welcome to CEDLEARN, a world of customized training programs in the field of emerging technologies. We have a gamut of programs covering Python Language, Data Analytics, Data Science, Artificial Intelligence, Full-Stack Development and Azure/AWS DevOps

    • What Exactly is Machine Learning?

      In simple form, machine learning is all about teaching the machines to learn from the data without explicitly programming. It means machines learn from data i.e. experience just the way we humans learn. Until now we thought that learning is a unique characteristic of living things. As part of machine learning you would use various algorithms and statistical models. Python programming language is widely used here. Machine learning is further classified into 3 types – Supervised, Unsupervised & Reinforcement learning. It is used in various domains such as Banking, Marketing, E-commerce, Education, Medical and so on, wherever there is data and you are interested in extracting useful insights from it for business decisions. Fraud detection, Customer churning, sales prediction, Cancel cell detection etc are a few examples of machine learning in the real life.

    • What is a Data Science Course?

      Data Science is a combination of Data Analytics and Machine Learning. It is all about working on the data to extract the insights from it so that the businesses could make informed decisions. Data Science course would give you the knowledge and skills required to extract the data, clean & manipulate it, use visualization techniques, develop statistical & machine learning models, etc to be the sought after professional. Imagine you are a manager at UBER. You are expected to make decisions related to the number of cars on the road, peak and non-peak pricing, predict the demand during holidays, customer churning, driver analytics and so on. It is humanly impossible to make decisions blindly without having Data Science models. This is the reason why every industry is heavily investing in data science models to be more profitable and competitive.

    • What is Data Analytics?

      Data Analytics is all about extract information from the available data for decision making. It involves Statistical Analysis, Visualization, Dashboarding, Business Intelligence, etc. It mostly deals with tools such as Power BI, Advanced Excel, IBM Cognos, etc. There no or minimum programming involves. Sometimes you would find Python as part of the Data Analytics as it could be used for visualization and analysis. This field is in high demand as not every organization is interested in building whereas, everyone is interested in analysing the data for decision making. Hence, we highly recommend this course for students even those who are from non-technical field. It is good starter to enter in to the world of Data Science where you could test your skills and proceed further.

    • What is Azure/AWS DevOps?

      Azure/AWS DevOps is a methodology that combines software development (Dev) and IT operations (Ops). It aims to shorten the systems development life cycle and deliver high-quality software continuously. DevOps practices help organizations automate and integrate processes between development and operations teams, allowing them to build, test, and release software more efficiently and reliably. Azure DevOps is Microsoft's solution for managing the entire DevOps lifecycle, while AWS offers a set of DevOps tools to automate software delivery and infrastructure management. Both platforms provide features such as Continuous Integration (CI), Continuous Delivery (CD), automated testing, and monitoring to enhance the speed and quality of software releases.

    • What Qualifications do I Need to Study Data Science?

      You do not need any specific qualification to know Data Science. For that matter, it is true for any course in IT. However, you must have logical thinking, few math skills, algorithmic thinking, loads of patience and a zeal to learn. Most of these requirements could be fulfilled if you are really interested. Of course you need a good trainer or a mentor to handhold throughout your journey towards Data Science. You could start with brushing up on Statistics and learning Python. Commit to the course which is based on project-based learning as mere knowledge would not help you. Practice is the key to being good at Programming or even Data Science. That is the reasons why we give a dashboard for every learner so that they could practice their skills regularly.

    • Is Data Science a Good Career?

      Indeed it is. If you look at the amount of data we are creating on a daily basis while using social media, e-commerce, transportation, online search and even at a retail store. Organizations are interested in processing these volumes of data to get insights so that they could make business decisions such as offering personalized services to the customers or aligning their prices or launching new products or such. This is the very reason why organizations are investing heavily in Data Science models. With this, there is increasing demand for professionals with Data Analytics or Data Science certification to be part of their team and solve business problems. As per the current market trends, Data Science would create 3 times more jobs in the next decade. Hence, it is good timing to think about Data Science as a career option.

    • What is Hybrid Learning?

      No worries. The intention is to teach Robotics and coding in a step way so that you would enjoy learning. The concepts are structured in a systematic way to facilitate learning and build confidence in your to work on the projects independently.

    • Do you offer a Job Guarantee program?

      There are two types of courses we offer one with job readiness and the other with a job guarantee. Even though the course content, projects and approach are the same for both the programs, the only difference lies in the post completion of the course. Irrespective of what type of course you pick, with or without a job guarantee we would train you with profile building, assessments, interview skills, mock interviews and so on. We have partnership with various organizations and also our students are currently working with various reputed organizations. In the job guarantee program we would ensure and work with the learners until they are placed. You would be assigned a career coordinator who would make sure that you are placed or you would get a refund. Currently the packages for a good Data Analyst or Data Scientist could start anywhere between 5L PA to 9L PA at the entry level.

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