Artificial Intelligence Associate

Overview

Course Description

Cyber Security Associate course students ko modern digital systems ki security, cyber threats, data protection aur ethical security practices ke baare me practical knowledge provide karta hai. Is course me cyber security ke core concepts ke saath vulnerability assessment, penetration testing aur cyber forensics jaise important areas cover kiye jate hain.

Students ko network security, system protection, cyber attack prevention, risk identification aur security monitoring ki understanding develop karvai jati hai, jisse ve real-world cyber security environments me efficiently work kar saken. Course ka objective industry-ready cyber security professionals tayar karna hai jo organizations ke digital infrastructure ko secure rakhne me contribute kar saken.

What you'll learn

Programming with Python
Conceptualizing Data Science with python
Data analysis and Visualization
Fundamentals of Machine Learning
Performance and Accuracy of Machine Learning models.
Employability Skills

Career Opportunities

Cyber Security Associate
Information Security Assistant
Security Operations Center (SOC) Analyst – Entry Level
Vulnerability Assessment Assistant
Cyber Security Support Executive
Network Security Assistant
IT Security Coordinator
Cyber Forensics Support Executive

Course Content

Installing and configuring Python IDE
Understanding Python syntax, data types, operators, control flow
Working with built-in data structures – lists, tuples, dictionaries, sets
Functions, modular programming and package management
Small project using multiple modules and packages

Introduction to Data Science concepts and tools
Preprocessing and cleaning raw data
Using NumPy for numerical operations and array handling
Statistical analysis using Python

Using Pandas for structured data analysis
Data Frames and Series in Pandas
Exploratory Data Analysis (EDA) techniques
Creating data visualizations using Matplotlib and Seaborn

Introduction to ML and learning types (supervised, unsupervised, reinforcement)
Setting up ML environment with Scikit-learn
Building and evaluating ML models

Predictive analysis with regression and classification
Statistical techniques for model building
Feature selection and evaluation metrics
End-to-end ML project implementation

About the instructor

Nicole Brown

UX/UI Designer

4.5

5Courses

12+ Lesson

9hr 30min

270,866 students enrolled

UI/UX Designer, with 7+ Years Experience. Guarantee of High Quality Work.

Skills: Web Design, UI Design, UX/UI Design, Mobile Design, User Interface Design, Sketch, Photoshop, GUI, Html, Css, Grid Systems, Typography, Minimal, Template, English, Bootstrap, Responsive Web Design, Pixel Perfect, Graphic Design, Corporate, Creative, Flat, Luxury and much more.

Available for:

Full Time Office Work
Remote Work
Freelance
Contract
Worldwide

Total Fees

18000

Enroll Now

Course Features

NSQF Level: 4.0

Duration: 450 hours

Apar Credits: 16

Government Recognized Certificate

Certificate of Completion

Eligibility

12th grade pass
Completed 2nd year of 3-year diploma (after 10th) and currently pursuing diploma
10th grade pass and currently in continuous schooling
10th grade pass with 2 years of relevant experience