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Full Stack Python

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 Python ML & AI Training Institute in Hyderabad

Course Overview

Master Full Stack Python, Machine Learning, and Artificial Intelligence with hands-on projects and expert mentorship at Mohansh Technologies, Hyderabad’s top-rated training institute. Build real-world AI applications and become job-ready in emerging tech.

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 Technologies, HTML Structure, Tags
  • Day 2: HTML Forms, Tables, Lists, Links, Semantic Elements
  • Day 3: CSS Fundamentals – Selectors, Colors, Fonts, Borders
  • Day 4: Box Model, Flexbox, Grid, Responsive Web Design
  • Day 5: JavaScript Basics – Variables, Functions, Loops, Arrays
  • Day 6: DOM Manipulation, Events, Form Validation

WEEK 2

  • Day 7: Advanced JS (ES6) – Arrow Functions, Promises, Async/Await
  • Day 8: Fetch API, JSON, LocalStorage, Event Handling
  • Day 9: React JS – Components, Props, State, Hooks
  • Day 10: React Project – Dynamic To-Do / Weather App
  • Day 11: Python Review – Syntax, Lists, Tuples, Dicts, Loops
  • Day 12: OOP Concepts, File Handling, Exception Handling

WEEK 3

  • Day 13: Flask Framework – Routes, Templates, Jinja2
  • Day 14: Flask Forms, Sessions, API Creation
  • Day 15: Django Introduction – MVT Architecture, App Setup
  • Day 16: Models, Views, Templates, Static Files
  • Day 17: Authentication, Middleware, Admin Customization
  • Day 18: CRUD Operations, Pagination, Permissions

WEEK 4

  • Day 19: Django REST Framework – Serializers & APIs
  • Day 20: Mini Project – Blog or Notes API Integration
  • Day 21: Introduction to Databases – SQL vs NoSQL
  • Day 22: MySQL Setup, Basic Queries, Joins
  • Day 23: Django ORM – Relationships, Filtering
  • Day 24: Data Migrations, Advanced ORM

WEEK 5

  • Day 25: MongoDB Basics – CRUD, Collections, JSON
  • Day 26: PyMongo Integration with Flask/Django
  • Day 27: Git, GitHub – Branching, Commits, Collaboration
  • Day 28: Docker – Containers, Images, App Packaging
  • Day 29: Cloud Deployment – AWS / Render / Vercel
  • Day 30: Integration Project – Full Stack Web App
  • Day 31: Introduction to ML – Workflow, Dataset Handling

WEEK 6

  • Day 32: NumPy & Pandas – Data Manipulation
  • Day 33: Data Cleaning, Encoding, Feature Scaling
  • Day 34: Visualization – Matplotlib & Seaborn
  • Day 35: Supervised Learning – Regression & Classification
  • Day 36: Decision Trees, Random Forest, KNN
  • Day 37: Unsupervised Learning – Clustering, PCA
  • Day 38: ML Model Deployment with Flask/Django APIs

WEEK 7

  • Day 39: Introduction to AI, DL, Neural Networks
  • Day 40: TensorFlow / Keras – Building ANN Models
  • Day 41: Natural Language Processing (NLP) Basics
  • Day 42: AI API Integration – Chatbot / Image Recognition
  • Day 43: Full Stack + AI Integration Project
  • Day 44: Final Project – Frontend + Backend + AI Integration, Testing
  • Day 45: Hosting, Resume Preparation, GitHub Portfolio & Mock Interview

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

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