Applied Data Science And AI/Machine Learning for Cybersecurity Professionals (SEC595)

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!

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.

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