If you've written even one line of Python, you are probably knowledgeable enough to get started! We will cover lists, arrays, tuples, dictionaries, comprehensions and then begin introducing the numpy variants.įollowing the Python refresher the course provides some theory followed immediately by hands-on exercises to give you just enough knowledge of SQL, MongoDB, and webscraping to get real work done. The only course prerequisite is a fundamental understanding of Python. The first necessary skill is the use of Python, our chosen language for this course. Since the first step in any data science or machine learning project is to acquire data, the balance of the day is focused on hands-on exercises to prepare the student for these tasks. This section introduces some of the terminology in the data science and machine learning fields, in addition to introducing a number of the technologies that are used as data sources. Model information security problems in useful ways.Jupyter notebooks of all of the labs and complete solutions.Understand and build Genetic Search Algorithms.Build and understand Convolutional Neural Networks.Understand and apply unsupervised learning/clustering methods.Perform mathematics-based threat hunting on your network.Apply statistical models to real world problems in meaningful ways.Data acquisition from SQL, NoSQL document stores, web scraping, and other common sources.The hands-on projects covered were selected to provide you a broad base from which to build your own machine learning solutions. 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. 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. 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. Unlike other courses in this space, this course is squarely centered on solving information security problems. 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. This course completely demystifies machine learning and data science. The problem is that, unless you have a degree in mathematics or data science, you're likely at the mercy of the vendors. 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.