Windows Users Introduction to Linux

About this Course

This is an introductory course in Linux. In this course you will learn where to get Linux, how to install it, and how to use it. The class focuses on learning how to use the Linux desktop to encourage you to start using it for day to day work. You will also learn some of the basics that you need for supporting Linux servers as well.

Introduction to Linux

Learning to use Linux for day to day use will help you become very comfortable with it so that you will find Linux fun, and also see the power of it. You will also build the solid foundation that you need to build on for becoming an incredible Linux system administrator too.

Basic knowledge
  • This is an introduction to Linux. So no previous Linux skill is needed. You should have basic skills in installing operating systems, and in computer usage
What you will learn
  • This is an introductory course in Linux. In this course you will learn where to get Linux, how to install it, and how to use it. The class focuses on learning how to use the Linux desktop to encourage you to start using it for day to day work. You will also learn some of the basics that you need for supporting Linux servers as well.
  • Learning to use Linux for day to day use will help you become very comfortable with it so that you will find Linux fun, and also see the power of it. You will also build the solid foundation that you need to build on for becoming an incredible Linux system administrator too.

To Read More:

Advertisements

Machine Learning, NLP & Python-Cut to the Chase

Prerequisites: No prerequisites, knowledge of some undergraduate level mathematics would help but is not mandatory. Working knowledge of Python would be helpful if you want to run the source code that is provided.

Taught by a Stanford-educated, ex-Googler and an IIT, IIM – educated ex-Flipkart lead analyst. This team has decades of practical experience in quant trading, analytics and e-commerce.

This course is a down-to-earth, shy but confident take on machine learning techniques that you can put to work today

Machine learning.PNG

Let’s parse that.

The course is down-to-earth : it makes everything as simple as possible – but not simpler

The course is shy but confident : It is authoritative, drawn from decades of practical experience -but shies away from needlessly complicating stuff.

You can put ML to work today : If Machine Learning is a car, this car will have you driving today. It won’t tell you what the carburetor is.

The course is very visual : most of the techniques are explained with the help of animations to help you understand better.

This course is practical as well : There are hundreds of lines of source code with comments that can be used directly to implement natural language processing and machine learning for text summarization, text classification in Python.

The course is also quirky. The examples are irreverent. Lots of little touches: repetition, zooming out so we remember the big picture, active learning with plenty of quizzes. There’s also a peppy soundtrack, and art – all shown by studies to improve cognition and recall.

machine learning 2

What’s Covered:

Machine Learning:

  • Supervised/Unsupervised learning, Classification, Clustering, Association Detection, Anomaly Detection, Dimensionality Reduction, Regression.
  • Naive Bayes, K-nearest neighbours, Support Vector Machines, Artificial Neural Networks, K-means, Hierarchical clustering, Principal Components Analysis, Linear regression, Logistics regression, Random variables, Bayes theorem, Bias-variance tradeoff

Natural Language Processing with Python:

  • Corpora, stopwords, sentence and word parsing, auto-summarization, sentiment analysis (as a special case of classification), TF-IDF, Document Distance, Text summarization, Text classification with Naive Bayes and K-Nearest Neighbours and Clustering with K-Means

Sentiment Analysis:

  • Why it’s useful, Approaches to solving – Rule-Based , ML-Based , Training , Feature Extraction, Sentiment Lexicons, Regular Expressions, Twitter API, Sentiment Analysis of Tweets with Python

Mitigating Overfitting with Ensemble Learning:

  • Decision trees and decision tree learning, Overfitting in decision trees, Techniques to mitigate overfitting (cross validation, regularization), Ensemble learning and Random forests
  • Recommendations: Content based filtering, Collaborative filtering and Association Rules learning
  • Get started with Deep learning: Apply Multi-layer perceptrons to the MNIST Digit recognition problem
  • A Note on Python: The code-alongs in this class all use Python 2.7. Source code (with copious amounts of comments) is attached as a resource with all the code-alongs. The source code has been provided for both Python 2 and Python 3 wherever possible

Who is the target audience?

  • Yep! Analytics professionals, modelers, big data professionals who haven’t had exposure to machine learning
  • Yep! Engineers who want to understand or learn machine learning and apply it to problems they are solving
  • Yep! Product managers who want to have intelligent conversations with data scientists and engineers about machine learning
  • Yep! Tech executives and investors who are interested in big data, machine learning or natural language processing
  • Yep! MBA graduates or business professionals who are looking to move to a heavily quantitative role
Basic knowledge
  • No prerequisites, knowledge of some undergraduate level mathematics would help but is not mandatory. Working knowledge of Python would be helpful if you want to run the source code that is provided
What you will learn
  • Identify situations that call for the use of Machine Learning
  • Understand which type of Machine learning problem you are solving and choose the appropriate solution
  • Use Machine Learning and Natural Language processing to solve problems like text classification, text summarization in Python

To Learn More:

How To Do Keyword Research For SEO & Ranking On Google

About this Course

Are you looking for more information on how to do keyword research for SEO and ranking your content on Google?

In this course we explain why keyword research is a critical first step in achieving results with your content.

Have you have ever produced a blog article and wondered why you were not getting any website traffic?

The simple answer is that your article may not contain keywords people are searching for!

In this course we take you step by step through every step needed to do the proper research needed to find keywords people are actually looking for on Google.

how-to-boost-SEO

In this course you will learn:

  • Why keyword research is the first thing you should do before producing any content on a website
  • How to use the Google Keyword Planner. This includes seeking out keywords, finding keyword volume, merging keywords, and working with bulk data.
  • Doing advanced keyword research and competition analysis with tools such as Long Tail Pro, Majestic, SEMRush, Ahrefs and Moz.
  • Understanding what Long Tail keywords are and how you can utilize these to create content that generates lots of traffic for your website.
  • How to use additional free sites like Quora, Soovle, UberSuggest, Google Trends and much more to do additional keyword research.
  • Determining commercial intent with your keywords – Learning if your content will encourage others to buy products from you.
  • Advanced competition analysis – Determine if a keyword is worth trying to rank and if it’s even possible for you based on the existing competition.

We even include a live case study of a perfect long tail keyword generating revenue with Amazon products through the Amazon affiliate program.

If you have ever wanted to learn more about keyword research this course includes everything you need to know about finding the best keywords out there!

Who this course is for:

  • If you are interested in content marketing or blogging this course is a must watch!
  • If you have been struggling with content ideas this course will help you discover what people are really looking for online
  • If you are not willing to spend time analyzing data to determine keyword volume and you have no interest in content marketing this course may not be for you

SEO

Basic knowledge
  • You will be shown various tools for Keyword research which are free but some are paid (not required)
  • You should have a Google Drive document ready to collect keyword data
  • A Google Adwords / Google Account for using the basic free keyword tools
What you will learn
  • Learn to use the Google Keyword Planner
  • Learn how to successfully find keywords for creating content around
  • Understand how to find keywords that people search for on Google
  • Learn how to utilize various tools for doing research on keywords
  • Understand what long tail keywords are
  • Understand why keyword research is important as a first step for SEO success
    About this Course

    Are you looking for more information on how to do keyword research for SEO and ranking your content on Google?

    In this course we explain why keyword research is a critical first step in achieving results with your content.

    Have you have ever produced a blog article and wondered why you were not getting any website traffic?

    The simple answer is that your article may not contain keywords people are searching for!

    In this course we take you step by step through every step needed to do the proper research needed to find keywords people are actually looking for on Google.

    In this course you will learn:

    • Why keyword research is the first thing you should do before producing any content on a website
    • How to use the Google Keyword Planner. This includes seeking out keywords, finding keyword volume, merging keywords, and working with bulk data.
    • Doing advanced keyword research and competition analysis with tools such as Long Tail Pro, Majestic, SEMRush, Ahrefs and Moz.
    • Understanding what Long Tail keywords are and how you can utilize these to create content that generates lots of traffic for your website.
    • How to use additional free sites like Quora, Soovle, UberSuggest, Google Trends and much more to do additional keyword research.
    • Determining commercial intent with your keywords – Learning if your content will encourage others to buy products from you.
    • Advanced competition analysis – Determine if a keyword is worth trying to rank and if it’s even possible for you based on the existing competition.

    We even include a live case study of a perfect long tail keyword generating revenue with Amazon products through the Amazon affiliate program.

    If you have ever wanted to learn more about keyword research this course includes everything you need to know about finding the best keywords out there!

    SEO getting your website

    Who this course is for:

    • If you are interested in content marketing or blogging this course is a must watch!
    • If you have been struggling with content ideas this course will help you discover what people are really looking for online
    • If you are not willing to spend time analyzing data to determine keyword volume and you have no interest in content marketing this course may not be for you
    Basic knowledge
    • You will be shown various tools for Keyword research which are free but some are paid (not required)
    • You should have a Google Drive document ready to collect keyword data
    • A Google Adwords / Google Account for using the basic free keyword tools
    What you will learn
    • Learn to use the Google Keyword Planner
    • Learn how to successfully find keywords for creating content around
    • Understand how to find keywords that people search for on Google
    • Learn how to utilize various tools for doing research on keywords
    • Understand what long tail keywords are
    • Understand why keyword research is important as a first step for SEO success

    To learn More:

Learn RabbitMQ: Asynchronous Messaging with Java and Spring

– “RabbitMQ is the most widely deployed open source message broker.” – Pivotal Software, 2018

Join me in this course to learn ins and outs of RabbitMQ!

If you want to learn RabbitMQ and how to develop with it using Java and Spring AMQP, this is the only course you need! 

From Exchanges to Queues, Bindings to Message Listeners, we’ll start by learning the pillars, corner stones of RabbitMQ and build on top of them with practical development for all these concepts using Java and Spring! 

java spring

I will walk you through the starting from scratch, the messaging itself! We’ll discover what messaging means and how it affects our architectural decisions and design considerations. Next up is the AMQP, Advanced Message Queueing Protocol. We’ll discover the benefits and reasons behind the popularity of AMQP and how it shaped the architecture of RabbitMQ from messaging concepts to client platforms making use of it.

While discovering the advantages of AMQP, we’ll then start discovering RabbitMQ and its architecture. We’ll learn Queues, Exchanges, Bindings, Routings, Publishers, Subscribers and much more about RabbitMQ!

After meeting with RabbitMQ through the concepts that it puts on the table, we’ll start preparing our environment for running RabbitMQ and developing applications using it. We’ll install all the necessary software for RabbitMQ and have it up and running on our machines both on Windows and MacOS.

When we finish preparing our environment for RabbitMQ, we’ll start discovering by RabbitMQ Management Dashboard. We’ll see and learn how RabbitMQ Dashboard helps us easily monitor and manage our RabbitMQ server. We will then send our first ever message to RabbitMQ!

After sending our message, we’ll learn how to create Queues, Exchanges and Bindings between them.

Now it’s time to start developing for RabbitMQ! We’ll learn everything we need to develop software using RabbitMQ starting with RabbitTemplate. RabbitTemplate helps us publish messages to RabbitMQ really easy and we’ll learn to use it by examples. From simple text messages to actual objects, we’ll learn to send any kind of messages.

The Complete JavaScript series with jQuery and Angular JS

We’ll then deepen our knowledge by developing actual Queues, Exchanges and Binding with Java and Spring! We’ll learn how to construct Queues, Exchanges, Bindings with Spring AMQP using both Annotations and Builder methods. We’re not going to finish it there and we’ll develop a message listener for specific queue that we also created programmatically.

We’ll both publish and listen to messages so we’ll developing a complete application from scratch just like we should in our professional applications!

Until this point, you’ll practically gain all the knowledge you need to develop applications with RabbitMQ. But we’ll not stop there and also think of an asynchronous messaging pipeline scenario where we send messages from one application and receive from another one. If you’re beginning to work with RabbitMQ or if you need to realize an asynchronous scenario for your next design, this part is especially valuable to you and you should definitely learn how to do this!

Below are some of the key metrics for RabbitMQ; if you’re still hesitant to take this course, please read these carefully:

  • RabbitMQ is the most widely deployed open source message broker or messaging middleware in other terms.
  • With more than 35,000 production deployments of RabbitMQ world-wide at small startups and large enterprises, RabbitMQ is the most popular open source message broker.
  • RabbitMQ is lightweight and easy to deploy on premises and in the cloud. It supports multiple messaging protocols. RabbitMQ can be deployed in distributed and federated configurations to meet high-scale, high-availability requirements.
  • RabbitMQ runs on many operating systems and cloud environments, and provides a wide range of developer tools for most popular languages.

I hope I’ll be seeing you in the course to teach you everything you need to develop applications with RabbitMQ!

Basic knowledge
  • Working knowledge of Java, Spring preferred
  • Any Java IDE (Intellij preferred)
What you will learn
  • Learn to build applications with RabbitMQ using Java and Spring!
  • Learn and Implement Topics, Queues, Exchanges and Bindings in RabbitMQ
  • Learn how to develop message listeners for specific queues and routings
  • Learn to design asynchronous, message-driven systems with RabbitMQ!
  • Learn and understand Message-Queueing
  • Learn and understand Advanced Message-Queueing Protocol or AMQP
  • Learn and understand how Advanced Message-Queueing Protocol works
  • Learn and understand the architecture of RabbitMQ

To Learn More:

Cyber Security Incident Response and Handling

About this Course

This course covers the six phases of incident handling and responding as follows:

  • Introduction: Includes the definition of an event, incident, as well as the difference between them
  • Preparation Phase: Shows the elements of preparation and the team building
  • Identification Phase: Demonstrates where identification occurs and the assessment for identification
  • Containment: Explains the deployment and categorization needed as well as the short/long- term actions taken
  • Eradication: Stresses on restoring systems and improving defenses
  • Recovery: Elaborates the validation and monitoring required for attacked systems
  • Lessons Learned: Confirms the importance of meeting as a team to fix and improve and to share our experiences with others.

Ethical hacking most advanced

 

Basic knowledge
  • Basic IT Knowledge
  • Basic Computer Knowledge
  • Basic Microsoft Windows Knowledge
What you will learn
  • The essentials of the incident response and handling process that enables IT beginners as well as security professionals to be professional incident handlers

To Read More:

Machine Learning In The Cloud With Azure Machine Learning

About this Course

The history of data science, machine learning, and artificial Intelligence is long, but it’s only recently that technology companies – both start-ups and tech giants across the globe have begun to get excited about it… Why? Because now it works. With the arrival of cloud computing and multi-core machines – we have enough compute capacity at our disposal to churn large volumes of data and dig out the hidden patterns contained in these mountains of data.

Machine learning

This technology comes in handy, especially when handling Big Data. Today, companies collect and accumulate data at massive, unmanageable rates for website clicks, credit card transactions, GPS trails, social media interactions, and so on. And it is becoming a challenge to process all the valuable information and use it in a meaningful way. This is where machine learning algorithms come into the picture. These algorithms use all the collected “past” data to learn patterns and predict results or insights that help us make better decisions backed by actual analysis.

You may have experienced various examples of Machine Learning in your daily life (in some cases without even realizing it). Take for example

Credit scoring, which helps the banks to decide whether to grant the loans to a particular customer or not – based on their credit history, historical loan applications, customers’ data and so on

Or the latest technological revolution from right from science fiction movies – the self-driving cars, which use Computer vision, image processing, and machine learning algorithms to learn from actual drivers’ behavior.

Or Amazon’s recommendation engine which recommends products based on buying patterns of millions of consumers.

In all these examples, machine learning is used to build models from historical data, to forecast the future events with an acceptable level of reliability. This concept is known as Predictive analytics. To get more accuracy in the analysis, we can also combine machine learning with other techniques such as data mining or statistical modeling.

This progress in the field of machine learning is great news for the tech industry and humanity in general.

But the downside is that there aren’t enough data scientists or machine learning engineers who understand these complex topics.

Well, what if there was an easy to use a web service in the cloud – which could do most of the heavy lifting for us? What if scaled dynamically based on our data volume and velocity?

robo4

The answer – is new cloud service from Microsoft called Azure Machine Learning. Azure Machine Learning is a cloud-based data science and machine learning service which is easy to use and is robust and scalable like other Azure cloud services. It provides visual and collaborative tools to create a predictive model which will be ready-to-consume on web services without worrying about the hardware or the VMs which perform the calculations.

The advantage of Azure ML is that it provides a UI-based interface and pre-defined algorithms that can be used to create a training model. And it also supports various programming and scripting languages like R and Python.

In this course, we will discuss Azure Machine Learning in detail. You will learn what features it provides and how it is used. We will explore how to process some real-world datasets and find some patterns in that dataset.

Do you know what it takes to build sophisticated machine learning models in the cloud?

How to expose these models in the form of web services?

Do you know how you can share your machine learning models with non-technical knowledge workers and hand them the power of data analysis?

These are some of the fundamental problems data scientists and engineers struggle with on a daily basis.

personal

This course teaches you how to design, deploy, configure and manage your machine learning models with Azure Machine Learning. The course will start with an introduction to the Azure ML toolset and features provided by it and then dive deeper into building some machine learning models based on some real-world problems.

If you’re serious about building scalable, flexible and powerful machine learning models in the cloud, then this course is for you.

These data science skills are in great demand, but there’s no easy way to acquire this knowledge. Rather than rely on hit and trial method, this course will provide you with all the information you need to get started with your machine learning projects.

 

Startups and technology companies pay big bucks for experience and skills in these technologies They demand data science and cloud engineers make sense of their dormant data collected on their servers – and in turn, you can demand top dollar for your abilities.

You may be a data science veteran or an enthusiast – if you invest your time and bring an eagerness to learn, we guarantee you real, actionable education at a fraction of the cost you can demand as a data science engineer or a consultant. We are confident your investment will come back to you many-fold in no time.

So, if you’re ready to make a change and learn how to build some cool machine learning models in the cloud, click the “Add to Cart” button below.

Look, if you’re serious about becoming an expert data engineer and generating a greater income for you and your family, it’s time to take action.

Imagine getting that promotion which you’ve been promised for the last two presidential terms. Imagine getting chased by recruiters looking for skilled and experienced engineers by companies that are desperately seeking help. We call those good problems to have.

Imagine getting a massive bump in your income because of your newly-acquired, in-demand skills.

That’s what we want for you. If that’s what you want for yourself, click the “Add to Cart” button below and get started today with our “Machine Learning In The Cloud With Azure Machine Learning”.

Let’s do this together!

Who is the target audience?

  • Data science enthusiasts
  • Software and IT engineers
  • Statisticians
  • Cloud engineers
  • Software architects
  • Technical and non-technical tech founders
Basic knowledge
  • Access to a free or paid account for Azure
  • Basic knowledge about cloud computing and data science
  • Basic knowledge about IT infrastructure setup
  • Desire to learn something new and continuous improvement
What you will learn
  • Learn about Azure Machine Learning
  • Learn about various machine learning algorithms supported by Azure Machine Learning
  • Learn how to build and run a machine learning experiment with real world datasets
  • Learn how to use classification machine learning algorithms
  • Learn how to use regression machine learning algorithms
  • Learn how to expose the Azure ML machine learning experiment as a web service or API
  • Learn how to integrate the Azure ML machine learning experiment API with a web application

To Read More:

Learn Ethical Hacking Advanced Level Using Kali linux

About this Course

Ethical hacking and penetration testing are testing the IT resources for a good cause and for the betterment of technology. This Kali linux tutorial will establish your understanding of all the fundamental concepts, processes, and procedures.. You will spend time concentrating on each knowledge area, and studying the tools and techniques, inputs, and outputs associated with each knowledge area.you will learn hacking concepts throughout this Kali Linux tutorials.

kali linux

In this Kali Linux tutorial you will learn how to become hacker to penetrate your network for defense it. In this online class you will learn hacking to secure your network and IT resources.This course is perfect Cyber Security Course to learn from zero.

In Introduction to Ethical Hacking, you will be introduced to various concepts on ethical hacking through this kali linux tutorials. You will receive an introduction to the basics of Risk Management and Disaster Recovery. As well as an introduction to Penetration Testing.In this kali linux tutorials you will learn from zero to hero.

You will gain a comprehensive understanding of vulnerability assessment and the tools used in this process. What kind of security measures do you take to protect your facilities, equipment, resources, personnel, and property from damage caused by unauthorized access? In this course, Physical Security, these are questions that we will be answering. Footprinting is the gathering of information related to a particular computer and its users and systems.

Reconnaissance is an exploration that is conducted to gain information. Network scanning is the scanning of public or private networks to find out which systems are running, their IP addresses, and which services they are running. In Port Scanning, you will learn how ports can be scanned, how a hacker can break into your network through the ports, and the countermeasures you can take to protect your device or network.

Banner grabbing is a technique used to grab information about computer systems on a network and the services running its open ports. In this course you will be introduced to enumeration and the many different uses it has in computer systems. This course will include demos on the different tools and uses of enumeration. In this online course (Kali linux tutorials) you will be learning the fundamentals of Linux and kali linux. We will be pairing this course with demos with a more in-depth look into some of the fundamentals and tools of Linux.

Pentesting is an attack on a system in hopes of finding security weaknesses. In this Kali linux course Configuring Kali Linux for Pentesting, you will be learning the steps to configure kali Linux for pentesting and tools used for pentesting on a Linux system. Whenever we login to a computer system, we provide information to identify ourselves. We refer to this as authentication. Ensure that you know everything involved in securing a Windows system against attack. During this course you’ll get into Windows passwords — how they’re created, how they’re stored, and different methods used to crack them.

You will take a good look at spyware, the activities it performs, different types of spyware, and the countermeasures needed in order to prevent hackers from utilizing these types of techniques against your company. You will also spend time studying different types of keyloggers through this kali linux course. There are three different types of keyloggers that we see used in today’s environments: hardware, software, and kernel/driver keyloggers. Covering Tracks will be going over various ways that attackers have at their disposal to cover any tracks that may lead to their unwanted eviction, or worse yet, to an audit trail that would lead directly back to them. Trojans and Backdoors is the course where our software is going to be going undercover.

You will discover what viruses and worms are and how they can infect computers and systems. Sniffers is our course where we take a look at Network Sniffing. Social engineering is the art of extorting employees for information.

Become familiar with the following concepts: denial-of-service, distributed denial-of-service, and how the denial-of-service and distributed denial-of-service attacks take place. In the course Session Hijacking, you will learn details about session hijacking, well-known techniques employed by aggressors, the steps involved in session hijacking, various types of session hijacking, tools for hijacking sessions, ways you can protect yourselves from session hijacking, and how pentesting can be used to identify vulnerabilities. Hacking Web and Application Servers, is a course that will give you a good idea about vulnerabilities and attacks available for web servers and web applications. In our course our course Advanced Exploitation Techniques, you will learn what advanced exploitation techniques are and how you can use them in your penetration testing. This course is completely Kali Linux tutorial.

Basic knowledge
  • Student must have knowledge about network technologies like servers,firewalls,routers,switches,operating systems
What you will learn
  • History of kali linux
  • Downloading Kali Linux
  • Installing Kali Linux
  • Configuring VMware Workstation
  • Updating Kali Linux
  • Managing Services in kali linux
  • Installing vulnerable machine in kali linux
  • Installing nessus
  • Installing cisco password cracker
  • Types of penetration testing
  • Target Scoping Concepts
  • Information gathering Concepts
  • Target discovery Concepts
  • Enumeration Concepts
  • Social Engineering Concepts
  • Vulnerability mappping Concepts
  • Target Exploitation Concepts
  • Privilege escalation Concepts
  • Maintaining Access Concepts
  • dig
  • host
  • dnsenum
  • dnsdict6
  • fierce
  • DMitry
  • Maltego
  • How to gather network routing information
  • Utilize the search engine
  • ping
  • arping
  • fping
  • hping3
  • nping
  • alive6
  • detect-new-ip6
  • passive_discovery6
  • nbtscan
  • OS fingerprinting
  • nmap
  • zenmap
  • SMB enumeration
  • SNMP enumeration
  • VPN enumeration
  • Openvas
  • Cisco Analysis
  • Fuzz Analysis
  • SMB Analysis
  • SNMP Analysis
  • Web Application Analysis
  • Social engineering toolkit
  • MSFConsole
  • MSFCLI
  • Ninja 101 drills
  • Password attack tools
  • Network spoofing tools
  • Network Sniffer
  • Using operating system backdoors
  • Tunneling tools
  • Creating Web Backdoors
  • FTP Server
  • SSH Server
  • Default Gateway
  • Configuring Network Interface Card
  • The Penetration testing lifecycle
  • Deploy metasploitable 2 into vm

To learn more: