Cybersecurity Data Science Training & Certification

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Cybersecurity Data Science Training & Certification

Data Science is one of the most in-demand professions today. It is also one of the most exciting and diverse IT occupations in the world, with attractive premium packages. The vast majority of cyber-attacks breach a company’s stored data and then utilize it fraudulently. Data security is crucial to cybersecurity. Cybersecurity EduCerts Data Science training course provides a revolutionary method to leveraging data science to detect, prevent, and mitigate cybersecurity risks.

Why This Course

Certified and experienced trainers provide 24 hours of instructor-led training.

Size: Small Batch 1: 1 Mentor Assistance Access to Pre-recorded Sessions

Why Enroll In Course?

The Cybersecurity Data Science Training Course offers a comprehensive understanding of cybersecurity principles and data science techniques. Participants learn to analyze cybersecurity data, leverage data-driven approaches, and develop practical skills through hands-on exercises. They gain insights into advanced topics such as anomaly detection and predictive analytics, preparing them for in-demand roles in cybersecurity and data science. The course certification validates their proficiency and enhances professional credibility, opening up diverse career opportunities. Overall, this course equips individuals to excel in addressing cybersecurity threats using data science methods.

Training Features

Live Interactive Learning

Lifetime Access

24x7 Support

Hands-On Project Based Learning

Industry Recognized Certification

Cloud

Course Curriculum

Introduction to Data Science Introduction to Cyber Security Python Basics

Statements and Loops
Creating Functions
Data Wrangling using Pandas and NumPy

Exploratory Data Analysis

Summary Statistics
Data Visualization
Missing Value detection
Outlier detection
Data Transformation
Splitting the data Into Training and Test Data

Machine Learning for Cyber Security

Data Dimensionality Reduction PCA Statistical Intuition and Implementation
Segregating data using clustering Statistical Intuition and Implementation
Training an XGBoost classifier
Analyzing time series using statsmodels Explanation and Implementation using statsmodels
Anomaly detection with Isolation Forest Explanation and Implementation
Natural language processing using a hashing vectorizer and Tf-Idf Explanation and Implementation
Hyperparameter tuning with scikit-optimize Implementation
Generating text using Markov chains

Email Cybersecurity Threats Detection

Introduction to detect spam with Perceptron
Introduction to Perceptron
Introduction to spam filters
Spam filter in action
Detecting spam with linear classifiers
How the Perceptron learns
A simple Perceptron-based spam filter
Pros and cons of Perceptron
Introduction to Spam detection with SVMs
SVM spam filter example
Introduction to Phishing detection with logistic regression and decision trees
Linear regression for spam detection
introduction to Logistic regression
Logistic Regression Implementation
Introduction to making decisions with trees
Phishing detection with decision trees
Spam detection with Naive Bayes
NLP with Naive Bayes Implementation

Malware Threat Detection

Introduction to Malware detection
Malware goes by many names
Malware analysis tools of the trade
Static malware analysis
Dynamic malware analysis
Hacking the PE file format
Introduction of Decision tree malware detectors
Malware detection with decision trees
Random Forest Malware classifier
Clustering malware with K-Means
K-Means steps and its advantages and disadvantages
Detecting metamorphic malware with HMMs Introductions
Polymorphic malware detection strategies
HMM Implementation

Advanced malware threat detection

Obfuscation Detection Python Implementation
Obfuscation Detection Python Explanation
Tracking malware drift Implementation
Tracking malware drift Explanation

Network Anomaly Detection

Turning service logs into datasets
Introduction to classification of network attacks
Detecting botnet topology
Introduction to different ML algorithms for botnet detection
Introduction to Gaussian anomaly detection
Gaussian anomaly detection Implementation

Securing Users Authentication

Introduction to Authentication abuse prevention
Fake login management- reactive versus predictive
Account reputation scoring
User authentication with keystroke recognition Introduction
User authentication with keystroke recognition Implementation
Biometric authentication with facial recognition Introduction
Dimensionality reduction with principal component analysis (PCA) Introduction
Eigenfaces Implementation

Automatic intrusion detection

Detecting DDos Attack
Credit Card fraud detection Introduction
Credit Card fraud detection Implementation
Counterfeit bank note detection Implementation
Ad blocking using machine learning Implementation
Wireless indoor localization Implementation
IoT device type identification using machine learning
Deep Face recognition

Securing and Attacking Data with Machine Learning

Assessing password security using ML
ML-based steganalysis Introduction
ML-based steganalysis Implementation
ML attacks on PUFs Introduction
ML attacks on PUFs Implementation
ML attacks on PUFs Explanation
HIPAA data breaches – data exploration and visualization

Projects

Online Transaction Fraud Detection
Fake News Detection
Fake Product Review Detection
Spam Email Detection
Credit Card Fraud Detection

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Certification

Certification in Cybersecurity Data Science

Completing the Cybersecurity Data Science Training Course awards a prestigious certification that validates expertise in cybersecurity and data science. This recognized certification demonstrates comprehensive understanding of cybersecurity principles, data analytics, machine learning, and data visualization. Participants gain the ability to effectively analyze, detect, and respond to cybersecurity threats using data science methodologies. This certification establishes individuals as trusted professionals in the field, enhancing marketability and opening diverse career opportunities as cybersecurity analysts, data scientists, or security consultants. It showcases proficiency in leveraging data-driven approaches to enhance threat detection and response capabilities, reflecting a commitment to excellence in addressing the evolving challenges of the digital landscape.

Online Training FAQs

Why Data Science with Us?

EduCerts is a prominent supplier of certification and upskilling training with alumni all around the world. Our teachers are industry professionals with years of expertise in various fields and jobs in Data Science. Our cutting-edge online training materials, as well as access to downloadable study aids and pre-recorded training sessions, will help you on your Data Science Learning journey.

Can you combine data science with cyber security?

Artificial intelligence and data science can significantly improve traditional cybersecurity.

Is data science required for cyber security?

While data science relies on cyber security for data integrity and protection, cyber security relies on data science to collect meaningful, actionable data that can be used to better safeguard systems, networks, and data.

What is the role of data analytics in cybersecurity?

When we discuss big data analytics in cyber security, we are referring to the capacity to collect large amounts of digital data. It operates by extracting, visualizing, and analyzing future insights in order to anticipate serious cyber threats and assaults.

What are the risks associated with big data?

large data poses security concerns—privacy and security are important concerns with large data. Bad actors can take use of big data. When data falls into the wrong hands, it may be exploited for phishing, fraud, and misinformation.

Course Description

Course Overview

Data science is becoming one of the most in-demand skills in the IT industry. In recent years, cybersecurity has experienced considerable technical and operational advancements. The Data Science for Cyber Security course from EduCerts is meant to be an all-in-one resource that may help you enhance your career. Examine all of the foundations of Data Science for Cyber Security while also making sure you’ve had enough exposure to more advanced subjects.

The key to automating and intelligent security systems is to extract security event patterns or insights from cybersecurity data and build a data-driven model around it. To interpret and assess actual phenomena with data, many scientific methodology, machine learning techniques, procedures, and systems are used. The data is obtained from trustworthy cybersecurity sources, and the analytics are utilized to complement the most recent data-driven patterns in order to give more effective security solutions.

Why Data Science for Cyber Security Training with EduCerts?

EduCerts is a global technology and security training and consulting firm that specializes in different IT security courses and services. Our Data Science for Cyber Security training course attempts to apply Data Science skills to cybersecurity concerns. EduCerts may provide you with the following advantages:

We can assist you in presenting your qualifications and job experience for the specific profile.
We provide a versatile training regimen.
Following the session, we provide recorded footage to each participant.
We offer post-training support.
Each applicant also receives a participation certificate.