Cybersecurity Data Science Projects for Students

Beginner Projects to Learn the Field and Build up Your Resume

What You'll Learn

Project for Students will guide you on the path to using machine learning to

✔ Classify and Detect Malware.
✔ Catch Network Intruders.
✔ Detect Insider Threats.
✔ Break CAPTCHAs.
✔ Construct an Evolutionary Fuzzer.
✔ Construct Adversarial Attacks on Deep Neural Networks.
✔ Impersonate Voice.
✔ Create DeepFakes.
✔ Generate Fake Reviews.

Course Description

Looking to enter the profession but don’t know where to start? Projects for Students will help you on the path to ultimately becoming a badass hacker and security expert who knows how to use machine learning to break and secure systems.

In this one-of-its-kind workbook, you will be guided on interesting and fun projects that will allow you to display your skills and growing knowledge. The projects are purposefully designed to be at the perfect balance of challenge (i.e., a beginner can complete them with a bit of patience) and interest so that solving them is sure to impress hiring managers, employers and co-workers.

The course uses python and tensorflow for deep learning. It is hands on and each project is immersive several-week experience. Studentsexpected to get their hands dirty with malware, neural networks and DeepFakes!

Who This Course Is For

– Students looking to learn the field of Cybersecurity Data Science

Requirements

☐ Basic programming in python.
☐ Basic knowledge of data science.

See What Students Have To Say

"A very crisp course and to the point! Course has covered almost everything which is required to novice data scientist. Well Curated course and expecting upgradation with explanation about cyber security world and the area where data scientist can play important role."

Rashmi Pandey

Senior Software Engineer (AI & computer vision)

 5/5

"The lectures are presented in an interesting and very clear manner. Warmly recommended."

Simon Keidar

Advocate

 5/5

"I recently took Cybersecurity Data Science by Emmanuel Tsukerman. This was the first course I have ever seen to combine 2 of my passions (cyber security and data science). I really enjoyed the content, it was enough to give you a good overview of the topics he covers."

Leon Rosenstein

Cybersecurity Data Scientist

 5/5

"This course provides an excellent overview of the intersection between ML and security. Should you want to dive into the models a bit deeper than in the videos, your python skills need to be above the recommended level, in my opinion. This course provides an excellent overview of what is possible and what areas to further study, but as stated, is just an introduction and overview."

Marnus van Staden

Operational Manager

 5/5

"Probably my favourite course i've taken on this platform. (And i've taken shiploads). Combining cyber security and data analysis is crucial but no one seems to be talking about it. Except the author. You have a fan for life brother. I've ordered your cookbook in pdf and hard copy so I can write out as many as I can. Studying this course I've realised my python is not as strong as I thought it was so I have jumped on sharpening that up so I can fully utilise your hard work before me. But knowing what I can do with the python library using these methods has me more excited than ever to have to learn it as seeing the benefits are the greatest motivators. If you are ever in Australia I would love to buy you a coffee/beer/ dinner to pick your brain. I have only just come across you but I already see you as a mentor. Also, can I pay to get on your newsletter? I've pretty much already brought everything else, so it would be a shame to have to buy the whole bundle to get access. PS. I dig your editing, I love banging out an instrumental when i'm getting stuck into some work haha."

Matty Bell

Principal Software Development Engineer

 5/5

"A practical course with straigthforward explanations that dive deep into the practical skills. I recommend having previous basic knowledge of machine learning and python for the course to be fluent and an open door to exploring new and deeper concepts. The instructor is clear in his explanations."

Darwin Patricio Cordova

Senior Android developer

 5/5

"I have an extensive data sciences background but am new to the cybersecurity environment and had previously taken a "red attack" intro course. This is helping me understand better how to analyze the results of malware data sets."

Mike Ensby

Data Scientist

 4.5/5

About Me

Dr. Emmanuel Tsukerman, Founder of ML4CS

Dr. Tsukerman graduated from Stanford University and UC Berkeley. His achievements include designing a machine-learning-based anti-ransomware product that won Top 10 Ransomware Products by PC Magazine as well as implementing a machine-learning-based malware detection system for Palo Alto Network’s WildFire service serving over 30,000 enterprise customers. Dr. Tsukerman is the author of the Machine Learning for Cybersecurity Cookbook, Cybersecurity Data Science and Machine Learning for Red Team Hackers Courses.