Malware Analysis & Incident Response for IT Technicians

Over this course, we'll be covering some of the ways that you can prevent and respond to IT security incidents on your organisation's network. Course topics include the following:

• An explanation of the key differences between malware analysis and incident response
• Known malware, online file analysis and tools that can be used to analyse running processes
• Unknown malware and how to recognise suspicious files, using heuristic activity detection and vulnerability analysis
• Incident prevention methods, including securing removable storage and an explanation of email filtering and analysis tools.
• Incident response methods, such as escalation procedures and service priorities.

Who this course is for:

IT Technicians who want to learn more about incident prevention, malware analysis and incident response

Requirements

To be an IT Technician with approximately 1-2 years of experience within the IT industry.

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Apply Natural Language Processing (NLP) with Python

Natural Language Processing (NLP) is a very interesting field associated with AI and is at the forefront of many useful applications like a chatbot. Knowledge of NLP is considered a necessity for those pursuing a career in AI. This course covers both the theory as well as the applications of NLP. Case studies are explained along with a walkthrough of the codes for a better understanding of the subject.

Requirements

Understanding of Python and basics of machine learning

Who this course is for:

Data Scientists, Python Programmers, ML Practitioners, IT Managers managing data science projects

Python developers interested in learning how to use Natural Language Processing

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 Mathematics & Statistics for Machine Learning

These concepts will help you to lay a strong foundation to build a thriving career in artificial intelligence.

This course teaches you the concepts mathematics and statistics but from an application perspective. It’s one thing to know about the concepts but it is another matter to understand the application of those concepts. Without this understanding, deploying and utilizing machine learning will always remain challenging.

You will learn concepts like measures of central tendency vs dispersion, hypothesis testing, population vs sample, outliers and many interesting concepts. You will also gain insights into gradient decent and mathematics behind many algorithms.

Requirements

No prior experience is required. We will start from the very basics.

Who this course is for:

Data Scientists, Python Programmers, ML Practitioners, IT Managers managing data science projects

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 Complete course in AutoCAD 2020 : 2D and 3D

This course contains a detailed explanation of AutoCAD commands and their applications to solve drafting and design problems. Every command is thoroughly explained with the help of examples and illustrations. This makes it easy for users to understand the functions and applications in the drawing. After going through this course, you will be able to use AutoCAD commands to make a drawing, dimension a drawing, applying constraints, insert texts and blocks, create 3D objects, generate drafting views of the model, 3d print a model, use CAD Standards, and advanced applications in AutoCAD software.

Requirements

Anyone with basic knowledge of Geometry concepts.

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