SANS SEC595: Applied Data Science and Machine Learning for Cybersecurity Professionals

علم داده، هوش مصنوعی و یادگیری ماشین فقط کلمات رایج فعلی نیستند، بلکه به سرعت در حال تبدیل شدن به یکی از ابزارهای اصلی امنیت اطلاعات هستند. دوره SANS SEC595 به صورت کامل یادگیری ماشین و علم داده را آموزش می دهد. بیش از 70 درصد از زمان کلاس صرف حل مشکلات یادگیری ماشین و علم داده به‌جای صحبت کردن در مورد آنها می‌ شود. بر خلاف سایر دوره ها، این دوره کاملاً بر حل مشکلات امنیت اطلاعات متمرکز دارد و تقریباً تمام موارد تئوری را آموزش می‌دهد، این دوره تعادل را ایجاد می‌کند. ما فقط تئوری و مبانی آموزشی را پوشش می‌دهیم. این دوره به تدریج ابزارهای مختلف آماری، احتمالی یا ریاضی را (در شکل کاربردی آنها) معرفی و به کار می‌برد و به شما امکان می‌دهد تا توانایی استفاده از آن ابزارها را یاد بگیرید. پروژه های عملی تحت پوشش انتخاب شدند تا پایگاه وسیعی را برای شما فراهم کنند تا راه حل های یادگیری ماشین خود را به صورت جامع تری فراگیرید…

Date: 2021
Price: $8,275 USD
Publisher: SANS
Format: Video + PDF + File

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

Additional Resources:

• Anaconda
• TensorFlow (and supporting libraries)
• Matplotlib
• VMWare Workstation/Player/Fusion