Cybersecurity Data Science
3.8 (74 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
622 students enrolled

Cybersecurity Data Science

Tools of the Future. Now.
3.8 (74 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
622 students enrolled
Last updated 6/2019
English
English [Auto-generated]
Price: $39.99
30-Day Money-Back Guarantee
This course includes
  • 1 hour on-demand video
  • 1 article
  • Full lifetime access
  • Access on mobile and TV
  • Assignments
  • Certificate of Completion
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What you'll learn
  • Use machine learning to classify malware.
  • Malware analysis 101.
  • Set up a cybersecurity lab environment.
  • Learn how to tackle data class imbalance.
  • Unsupervised anomaly detection.
  • End-to-end deep neural networks for malware classification.
  • Create a machine learning Intrusion Detection System (IDS).
  • Employ machine learning for offensive security.
  • Learn how to address False Positive constraints.
  • Break a CAPTCHA system using machine learning.
Requirements
  • Basic programming in python.
  • Basic knowledge of data science.
Description

The best of the best badass hackers and security experts are using machine learning to break and secure systems. This course has everything you need to join their ranks.

In this one-of-its-kind course, we will be covering all from the fundamentals of cybersecurity data science, to the state of the art. We will be setting up a cybersecurity lab, building classifiers to detect malware, training deep neural networks and even breaking CAPTCHA systems using machine learning.

If you've tried to enter the super hot field of cybersecurity and machine learning, but faced rejection after rejection, needing experience to get experience, feeling hopeless that the demand and pay are so high, but nothing you are doing is letting you in, this is your chance to gain an edge over the competition. This is your chance to get credentials and real experience.

If you are looking to break into the field of cybersecurity data science, pick up on the bleeding edge tools, and become the best in the field of cybersecurity, this course is for you.

We will be using python and scikit learn for majority of our machine learning, and keras, a wrapper for tensorflow, for deep learning. This course is hands on and practical. Consequently, a student is expected to put in the work and not be shy about getting their hands dirty with some malware!

If you still haven't chosen to enroll, you might be thinking:

- I'm trying to get a job in cybersecurity as a data scientist. Will this help me get one? Yes, and if 6 months after completing this course you're not able to break into the field, message me and I will personally refund you via PayPal. Just make sure to use the coupon code from my ML4CS website so I can give you back the full sum.

- What if this course sucks. I don't want to take another boring course. If you find the course boring, no worries. Quickly press the pause button and get your money back using the 30-day money-back guarantee. Send me a message after letting me know my course is boring and I'll try to make future content more interesting.

- Do I need to know stuff about cybersecurity? Because I don't. Nop. I'll teach you everything you need to know. You don't need to know jack-squat about cybersecurity.

- I'm not very good at coding in Python. You can find the code repo for this course in my github repo. I'll be walking you through this code and you can play around with it on your own. But if it's still looking too complicated, no worries, come back once you've leveled-up your Python chops.

- What if I am stuck on understanding something. Who is going to help me? I don't know anyone who knows this stuff. If you have a question about the course, use the Q&A and I promise to answer your question. I have a 100% response rate so far and I plan on continuing it. If you have a question about cybersecurity data science not directly pertaining to the course and you are a student of mine, you can use the ML4CS forum and I or someone else on the forum will answer your question.

Who this course is for:
  • Data scientists curious to apply the craft to the field of cybersecurity.
  • Cybersecurity experts curious to see how data science can be applied to cybersecurity.
Course content
Expand all 26 lectures 58:26
+ Machine learning and Malware Detection
17 lectures 46:15
In this assignment, we setup a virtual lab environment.
Setting Up a Lab Environment - Assignment
7 questions
Obtaining a Benign Dataset
01:44
Malware Analysis 101
03:56
In this assignment, we will get our hands dirty with some malware analysis.
Malware Analysis 101 - Assignment
5 questions
PE File - Quiz
2 questions
Installing the Pefile Library
00:27
In this assignment, we will create a corpus of DLL import tables to be used for training a classifier.
Preparing a Corpus Using pefile - Assignment
2 questions
TF-IDF
02:53
Creating a Train-Test Split
00:57
Training a Classifier
01:57
In this assignment, we will create a model to predict whether samples are benign or malicious.
Training a Classifier - Assignment
6 questions
Handling Type I and Type II Errors
02:32
N-grams
03:17
In this assignment, we will become familiar with the Natural Language Processing technique of N-grams.
N-grams - Assignment
4 questions
Hash-Grams
03:01
Building an N-gram Classifier
02:32
MalConv: Deep Learning on Executables
05:23
Section 1 - Conclusion
00:38
+ Machine Learning and Intrusion Detection
3 lectures 05:50
The KDD Cup Dataset
01:16
Isolation Forest
03:57
Section 2 - Conclusion
00:37
+ Machine Learning and Offensive Security
5 lectures 04:47
Really Simple CAPTCHA
01:02
In this assignment, we will get acquainted with Really Simple CAPTCHA and download a CAPTCHA dataset.
Really Simple CAPTCHA - Assignment
2 questions
Preprocessing CAPTCHAs
01:13
Training a CAPTCHA Recognizer
01:17
Course Conclusion
00:52
Optional: Research Projects in Cybersecurity Data Science
00:23