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Full Stack MERN AI

The Mohansh Technology Cyber Security Course in Hyderabad equips students with the most effective techniques for infrastructure and business protection.

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Full Stack MERN AI Training Institute in Hyderabad

Course Overview

Master the power of MERN Stack (MongoDB, Express, React, Node.js) combined with Artificial Intelligence (AI) at Mohansh Technologies, Hyderabad’s leading training institute for future-ready developers.
Gain hands-on experience, work on real-world projects, and become a job-ready Full Stack AI Developer.

Key Skills:

Foundations of KYC & AML

  • Understanding Know Your Customer (KYC) principles.
  • Anti-Money Laundering (AML) frameworks and compliance basics.
  • Importance of AML/KYC in financial institutions.

Global & Regional Regulations

  • FATF guidelines, Bank Secrecy Act, USA PATRIOT Act
  • EU AML Directives, OFAC compliance
  • Indian regulations: PMLA, RBI & SEBI guidelines, FIU-IND

Customer Due Diligence (CDD)

  • Standard CDD vs Enhanced Due Diligence (EDD)
  • Simplified KYC (low-value accounts)
  • High-risk customer assessment

AML Monitoring & Reporting

  • Money laundering stages: Placement, Layering, Integration
  • Suspicious Activity Reporting (SARs)
  • Transaction monitoring systems (TMS)

Fraud Detection & Prevention

  • Identifying red flags in customer profiles
  • Screening for Politically Exposed Persons (PEPs)
  • Case studies of real-world financial frauds

Technology in AML & KYC

  • Role of AI & Machine Learning in fraud detection
  • Blockchain & RegTech solutions for compliance
  • Identity verification tools (Aadhaar eKYC, biometrics, video KYC)

Compliance & Ethics

  • Regulatory reporting requirements
  • Maintaining ethical standards in compliance roles
  • Internal audit & compliance culture

Career & Job Readiness

  • AML/KYC job roles: Analyst, Investigator, Compliance Officer
  • Key tools: Actimize, SAS, Oracle Mantas, Excel/SQL basics
  • Industry demand for AML & KYC professionals (banks, fintechs, consulting firms)

45 DAYS FREE ONLINE CLASSES

WEEK 1

  • Day 1: Introduction to Web Development, HTML Structure, Tags
  • Day 2: Forms, Lists, Tables, Images, Semantic Elements
  • Day 3: CSS Basics – Selectors, Colors, Fonts, Box Model
  • Day 4: Flexbox, Grid, Responsive Design, Media Queries
  • Day 5: JavaScript Basics – Variables, Functions, Loops
  • Day 6: DOM Manipulation, Events, Form Validation

WEEK 2

  • Day 7: ES6 Features – Arrow Functions, Promises, Async/Await
  • Day 8: React JS Basics – Components, JSX, Props, State
  • Day 9: React Hooks, Events, Conditional Rendering
  • Day 10: React Project – Mini App (To-Do / Weather App)
  • Day 11: Node.js Introduction, npm & package.json
  • Day 12: Core Modules – fs, path, http

WEEK 3

  • Day 13: Express.js Basics – Routing, Middleware
  • Day 14: Express Router, Error Handling, Template Engines
  • Day 15: Building RESTful APIs (GET, POST, PUT, DELETE)
  • Day 16: Handling Forms & JSON Requests, CORS
  • Day 17: Authentication with JWT & bcrypt
  • Day 18: File Uploads, Image Handling (Multer)

WEEK 4

  • Day 19: Connecting Express to MongoDB
  • Day 20: Mini Project – User Auth & Blog API
  • Day 21: MongoDB Overview, Collections & Documents
  • Day 22: CRUD Operations with Mongo Shell & Compass
  • Day 23: Mongoose – Schema & Model Creation
  • Day 24: Relationships & Data Validation

WEEK 5

  • Day 25: Aggregations & Indexes
  • Day 26: Connecting Frontend (React) with Backend (Node)
  • Day 27: API Testing with Postman, Axios in React
  • Day 28: JWT Auth Flow – Login, Register, Protected Routes
  • Day 29: Deployment Basics – Render, Vercel, GitHub
  • Day 30: MERN Mini Project – E-Commerce or Blog App
  • Day 31: Introduction to ML, AI Concepts, Python Environment

WEEK 6

  • Day 32: Data Preprocessing with NumPy & Pandas
  • Day 33: Data Cleaning, Encoding, Feature Scaling
  • Day 34: Visualization using Matplotlib & Seaborn
  • Day 35: Supervised Learning – Regression, Classification
  • Day 36: Unsupervised Learning – Clustering, PCA
  • Day 37: Model Training & Evaluation with Scikit-Learn
  • Day 38: Saving Models with Pickle / Joblib

WEEK 7

  • Day 39: Building a Flask API for ML Model Serving
  • Day 40: Node.js ↔ Flask Integration + React Front End Connection
  • Day 41: Capstone Project Planning – Architecture & Tech Stack
  • Day 42: Backend + ML Integration (API Layer)
  • Day 43: Frontend Integration & Testing
  • Day 44: Deployment on Cloud (AWS, Render, Vercel)
  • Day 45: Resume Building, GitHub Portfolio, Mock Interview Prep

Flat No: 302, 3rd Floor, Namdev Block, Prime Hospital Line, Ameerpet, Hyderabad-38

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