100% Job Guarantee Training Program

100% Job Guarantee Training Program – Learn from Industry Experts
AI isn’t just for techies or researchers anymore — it’s for everyone who wants a secure career in today’s tech-driven world. Whether you’re a student, fresher, job seeker, entrepreneur, or working professional, this 5-hour hands-on training program offers guaranteed job placement and real-world learning with top industry experts. Discover the most in-demand AI tools that are transforming how we work, create, and communicate — and build a career with confidence.

             ✅ Who Should Join?

• • 🎓 Students & Freshers looking to start a career with hands-on, job-ready skills
  • 👨‍💼 Working professionals aiming to switch careers or upskill in high-demand fields
  • 💼 Job seekers struggling to land interviews or crack competitive roles
  • 🚀 Entrepreneurs & Freelancers who want to leverage practical skills to grow their business
  • 🧑‍💻 Non-tech background individuals who want to transition into tech or digital roles
  • 📉 Career break returnees ready to re-enter the job market with updated expertise
  • 🔍 Anyone serious about landing a high-growth job with expert mentorship and placement support

Why This Workshop is a Game-Changer

• Get trained by professionals working in top companies

• Learn high-demand skills with real-world applications

• No coding or technical background required

• Industry-approved curriculum with hands-on training

• Work on live projects & portfolio-building assignments

• Guaranteed job placement support after course completion

1. Generative AI / Data Science / Data Analytics / AI & ML (Combined Track – ~6-9 Months)

This track focuses on the cutting edge of data and AI, preparing you for roles like Data Scientist, Machine Learning Engineer, AI Product Developer, or Data Analyst.

Month 1: Fundamentals of Programming & Data

• Module 1: Python for Data Science – Introduction to Python programming, data types, control flow, functions, object-oriented concepts. Focus on libraries like NumPy and Pandas for data manipulation.

• Module 2: SQL & Database Essentials – Relational databases, SQL queries (CRUD operations, joins, subqueries), database design principles. Introduction to NoSQL databases.

• Module 3: Statistics & Probability for Data Science – Descriptive and inferential statistics, probability distributions, hypothesis testing.

Month 2: Core Data Science & Machine Learning

• Module 4: Exploratory Data Analysis (EDA) & Visualization – Data cleaning, preprocessing, feature engineering. Data visualization with Matplotlib, Seaborn, and potentially Tableau/Power BI.

• Module 5: Introduction to Machine Learning – Supervised learning (linear/logistic regression, decision trees, k-NN), unsupervised learning (k-means clustering), model evaluation metrics.

• Module 6: Advanced Machine Learning Techniques – Ensemble methods (Random Forests, Gradient Boosting), Support Vector Machines (SVMs).

Month 3: Deep Learning & AI Fundamentals

• Module 7: Deep Learning Foundations – Introduction to neural networks, activation functions, backpropagation. Frameworks like TensorFlow or PyTorch.

• Module 8: Convolutional Neural Networks (CNNs) – Image classification, object detection.

• Module 9: Recurrent Neural Networks (RNNs) & NLP Basics – Sequence data, text processing, introduction to Natural Language Processing (NLP).

Month 4: Generative AI & Advanced AI Concepts

• Module 10: Generative AI Principles – Understanding different types of generative models (GANs, VAEs, Transformers).

• Module 11: Large Language Models (LLMs) & Prompt Engineering – Working with pre-trained LLMs, fine-tuning, ethical considerations in AI.

• Module 12: Real-time AI Product Development Concepts – AI product lifecycle, data pipelines for AI, deployment strategies.

Month 5-6 (or beyond): Real-time AI Product Building & Capstone Project

• Module 13: MLOps & Deployment – Tools and practices for deploying, monitoring, and maintaining ML models in production (e.g., Docker, Kubernetes, cloud services).

• Module 14: Cloud Platforms for AI (AWS/GCP/Azure) – Leveraging cloud services for data storage, processing, and deploying AI/ML models.

• Module 15: AI Ethics & Responsible AI – Bias detection, fairness, transparency, and accountability in AI systems.

• Module 16: Capstone Project – Work on a real-time, end-to-end AI product, applying all learned concepts from data collection to deployment. Crucial for building a portfolio.

2. Full Stack Development: Java / Python / MERN (Separate Tracks – ~4-6 Months Each)

These tracks prepare you for roles as a Full Stack Developer, capable of building and deploying complete web applications.

2a. Full Stack Development (Java Track)

Month 1: Frontend Fundamentals & Core Java

• Module 1: HTML5, CSS3, JavaScript Basics – Structuring web pages, styling, responsive design, basic interactivity.

• Module 2: Core Java Programming – Java syntax, OOPs concepts, collections, exception handling, multithreading.

• Module 3: Version Control with Git & GitHub – Collaborative development, branching, merging, pull requests.

Month 2: Advanced Frontend & Java Backend Basics

• Module 4: Frontend Framework (e.g., React/Angular/Vue.js) – Building dynamic user interfaces, component-based architecture, state management.

• Module 5: JDBC & Database Integration – Connecting Java applications to databases (e.g., MySQL, PostgreSQL), SQL queries.

• Module 6: Servlets & JSP – Fundamentals of web applications with Java, handling HTTP requests and responses.

Month 3: Spring Framework & RESTful APIs

• Module 7: Spring Core & Spring Boot – IoC, DI, developing RESTful APIs with Spring Boot.

• Module 8: Spring Data JPA & Hibernate – Object-Relational Mapping (ORM) for database interaction.

• Module 9: API Testing & Security Basics – Postman for API testing, basic security concepts (authentication, authorization).

Month 4: Project Development & Deployment

• Module 10: Microservices Architecture (Introduction) – Understanding microservices concepts for scalable applications.

• Module 11: Deployment & DevOps Fundamentals (AWS/Docker) – Deploying Java applications to cloud platforms, introduction to Docker.

• Module 12: Full Stack Java Capstone Project – Build a complete web application from frontend to backend, integrating all learned technologies.

2b. Full Stack Development (Python Track)

Month 1: Frontend Fundamentals & Core Python

• Module 1: HTML5, CSS3, JavaScript Basics – Structuring web pages, styling, responsive design, basic interactivity.

• Module 2: Core Python Programming – Python syntax, OOPs concepts, data structures, functions.

• Module 3: Version Control with Git & GitHub – Collaborative development, branching, merging, pull requests.

Month 2: Advanced Frontend & Python Web Framework

• Outcomes You Can Expect

1. Get trained by industry experts with real-world experience

2. Secure your future with a 100% job guarantee upon program completion

3. Master in-demand skills through hands-on, practical training

4. Build a strong portfolio to showcase your expertise to employers

5. Boost your resume and LinkedIn with job-ready skills for any career path