CompTIA Security+ Study Guides And Books

 

CompTIA Security+ certification exam can be passed easily with the right amount of preparation. Here are some CompTIA Security+ study guides and books that can help prepare for the CompTIA Security+ certification exam.

 

1. The Official CompTIA Security+ Certification Self-Paced Study Guide (Exam SY0-601)

Author: James Pengelly

The book The Official CompTIA Security+ Certification Self-Paced Study Guide (Exam SY0-601)
is developed and endorsed by CompTIA. It covers all exam topics and teaches the essential skills that are required to pass the CompTIA Security+ SY0-601 exam. This book is highly recommended for candidates who are preparing for the CompTIA Security+ SY0-601 certification exam.

How to buy the book?

The book is available on Amazon.

 

2. CompTIA Security+: SY0-601 Certification Guide

Author: Ian Neil

The book CompTIA Security+: SY0-601 Certification Guide is also highly recommended for candidates preparing for the CompTIA Security+ certification exam. The book covers all exam objectives and covers all the topics in an easy to understand manner. It also contains several practice test questions.

How to buy the book?

The book is available on Amazon.

 

3. Web Application Vulnerabilities And Prevention

Author: Amrita Mitra

The book Web Application Vulnerabilities And Prevention explains different web application vulnerabilities like buffer overflow, SQL injection, Cross-Site Request Forgery, JSON Hijacking, Command Injection, CRLF Injection, PHP Object Injection, etc. The book covers all topics based on the latest CompTIA Security+ syllabus in mind. This book is highly recommended for candidates who are preparing for the CompTIA Security+ certification exam and want to learn about various web application attacks and how to prevent them.

How to buy the book?

The book is available on Amazon. Details can be found here.

 

4. The Security Buddy Premium Membership

The Security Buddy provides a CompTIA Security+ certification course that covers the syllabus of the latest CompTIA Security+ certification exam SY0-601. The full course is available to The Security Buddy premium members only.

Moreover, The Security Buddy website contains various articles on cyber security. Several hundred articles are written for candidates preparing for certification exams like the CompTIA Security+, CCNA, or CCNP. The articles cover topics like malware, network security, phishing, encryption, data breaches and prevention, ransomware, etc. The Security Buddy Premium Membership is highly recommended for candidates who are preparing for the CompTIA Security+ certification exam as well as candidates who are preparing for Cisco CCNA or CCNP certification exam.

Readers can find more information here:

The Security Buddy Membership Plan

The Security Buddy CompTIA Security+ certification course as per the latest syllabus SY0-601

Articles on the Cisco CCNA certification exam

Articles on the Cisco CCNP certification exam

All Articles – The Security Buddy

Cyber Security Tutorial – The Security Buddy

Calculate the pseudoinverse of a matrix using Python

What is the pseudoinverse of a matrix? We know that if A is a square matrix with full rank, then A-1 is said to be the inverse of A if the following condition holds: $latex AA^{-1}=A^{-1}A=I $ The pseudoinverse or the Moore-Penrose inverse of a matrix is a...

Cholesky decomposition using Python

What is Cholesky decomposition? A square matrix A is said to have Cholesky decomposition if it can be written as a product of a lower triangular matrix and its conjugate transpose. $latex A=LL^{*} $ If all the entries of A are real numbers, then the conjugate...

Tensor Hadamard Product using Python

In one of our previous articles, we already discussed what the Hadamard product in linear algebra is. We discussed that if A and B are two matrices of size mxn, then the Hadamard product of A and B is another mxn matrix C such that: $latex H_{i,j}=A_{i,j} \times...

Perform tensor addition and subtraction using Python

We can use numpy nd-array to create a tensor in Python. We can use the following Python code to perform tensor addition and subtraction. import numpy A = numpy.random.randint(low=1, high=10, size=(3, 3, 3)) B = numpy.random.randint(low=1, high=10, size=(3, 3, 3)) C =...

How to create a tensor using Python?

What is a tensor? A tensor is a generalization of vectors and matrices. It is easily understood as a multidimensional array. For example, in machine learning, we can organize data in an m-way array and refer it as a data tensor. Data related to images, sounds, movies,...

How to combine NumPy arrays using horizontal stack?

We can use the hstack() function from the numpy module to combine two or more NumPy arrays horizontally. For example, we can use the following Python code to combine three NumPy arrays horizontally. import numpy A = numpy.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) B =...

How to combine NumPy arrays using vertical stack?

Let’s say we have two or more NumPy arrays. We can combine these NumPy arrays vertically using the vstack() function from the numpy module. For example, we can use the following Python code to combine three NumPy arrays vertically. import numpy A = numpy.array([[1, 2,...

Singular Value Decomposition (SVD) using Python

What is Singular Value Decomposition (SVD)? Let A be an mxn rectangular matrix. Using Singular Value Decomposition (SVD), we can decompose the matrix A in the following way: $latex A_{m \times n}=U_{m \times m}S_{m \times n}V_{n \times n}^T $ Here, U is an mxm matrix....

Eigen decomposition of a square matrix using Python

Let A be a square matrix. Let’s say A has k eigenvalues λ1, λ2, ... λk. And the corresponding eigenvectors are X1, X2, ... Xk. $latex X_1=\begin{bmatrix} x_{11} \\ x_{21} \\ x_{31} \\ ... \\ x_{k1} \end{bmatrix} \\ X_2=\begin{bmatrix} x_{12} \\ x_{22} \\ x_{32} \\ ......

How to calculate eigenvalues and eigenvectors using Python?

In our previous article, we discussed what eigen values and eigenvectors of a square matrix are and how we can calculate the eigenvalues and eigenvectors of a square matrix mathematically. We discussed that if A is a square matrix, then $latex (A- \lambda I) \vec{u}=0...

Not a premium member yet?

Please follow the link below to buy The Security Buddy Premium Membership.

Featured Posts

Translate »