Artificial Intelligence Application Developer

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
Fundamentals of Deep Learning
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 programming environment for python
Writing basic programs and understanding datatypes, operators, looping constructs, functions
Exploring various data structures
Learn to work on modules and packages

Concept of Data Science and tools used
Pre- Processing Concepts in Data Science
Introduction to Numpy and Working on N-d arrays
Learning Analysis on Numpy
Exploring Image handling using Numpy

Introduction to Pandas
Exploring Data Frames and Series
Learning EDA and Data Analysis
Performing Analysis on datasets
Introduction to Visualization and Learning Tools for making Graphs and plots
Exploring analysis through visualization

ntroduction to Machine Learning
Learning various ML categories
Learning to build models on datasets

Implement Predictive Analysis using various Regression and Classification algorithms
Learn and apply statistics used in Machine Learning
Using various metrics and Feature Engineering techniques
Develop and Implement Project in Predictive Analysis using ML

Understand and implement Deep Learning using Neural Networks
Work in Computer Vision using CNN and implement Image based models
Understand NLP and implement Natural Language Processing algorithms

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