Genre: eLearning | Language: English | Size: 38.05 GB + 4.47 GB + 58.45 MB

SEC595 provides students with a crash-course introduction to practical data science, statistics, probability, and machine learning. The course is structured as a series of short discussions with extensive hands-on labs that help students to develop useful intuitive understandings of how these concepts relate and can be used to solve real-world problems. If you’ve never done anything with data science or machine learning but want to use these techniques, this is definitely the course for you! 30 Hands-on Labs

What You Will Learn

Data Science, Artificial Intelligence, and Machine Learning aren’t just the current buzzwords, they are fast becoming one of the primary tools in our information security arsenal. The problem is that, unless you have a degree in mathematics or data science, you’re likely at the mercy of the vendors. This course completely demystifies machine learning and data science. More than 70% of the time in class is spent solving machine learning and data science problems hands-on rather than just talking about them.

Unlike other courses in this space, this course is squarely centered on solving information security problems. Where other courses tend to be at the extremes, teaching almost all theory or solving trivial problems that don’t translate into the real world, this course strikes a balance. We cover only the theory and math fundamentals that you absolutely must know, and only in so far as they apply to the techniques that we then put into practice. The course progressively introduces and applies various statistic, probabilistic, or mathematic tools (in their applied form), allowing you to leave with the ability to use those tools. The hands-on projects covered were selected to provide you a broad base from which to build your own machine learning solutions.

Major topics covered include:

Data acquisition from SQL, NoSQL document stores, web scraping, and other common sources

Data exploration and visualization

Descriptive statistics

Inferential statistics and probability

Bayesian inference

Unsupervised learning and clustering

Deep learning neural networks

Autoencoders

Loss functions

Convolutional networks

Embedding layers

BUSINESS TAKEAWAYS:

Thise course will help your organization:

Generate useful visualization dashboards

Solve problems with Neural networks

Improve the effectiveness, efficiency, and success of cybersecurity initiatives

Build custom machine learning solutions for your organization’s specific needs

You Will Be Able To:

Apply statistical models to real world problems in meaningful ways

Generate visualizations of your data

Perform mathematics-based threat hunting on your network

Understand and apply unsupervised learning/clustering methods

Build Deep Learning Neural Networks

Build and understand Convolutional Neural Networks

Understand and build Genetic Search Algorithms

You Will Receive With This Course:

A supporting virtual machine

Jupyter notebooks of all of the labs and complete solutions

This Course Will Prepare You To:

Build AI anomaly detection tools

Model information security problems in useful ways

Build useful visualization dashboards

Solve problems with Neural networks

Happy Learning!!

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