Machine Learning refers to computers changing the way they perform tasks by automatically learning from new data without the assistance of humans. It assists in analyzing patterns, allowing cybersecurity professionals to quickly understand and avoid similar threats. This bootcamp from InfosecTrain will teach you the basics of Machine Learning, Python, and most importantly the application of Machine Learning in Cybersecurity.
When: 30th Nov – 02nd Dec 2022 08.00 -11.00 PM (IST)
Machine Learning can assist businesses in better analyzing threats and responding to security incidents. It could also help automate more unskilled tasks previously performed by overburdened and sometimes under-skilled security teams. As a result, Machine Learning in security is a rapidly growing trend. Adequate cyber security is now nearly impossible without heavily relying on Machine Learning. Those candidates who want to make their career more secure will benefit significantly from this bootcamp.
Agenda for the bootcamp
Introduction to Python
â€¢ How to launch Jupyter Notebook
â€¢ Shortcut keys of Jupyter Notebook
â€¢ Installation of Anaconda
â€¢ Basics of Python
â€¢ Important packages of python for Machine Learning
â€¢ Introduction to Machine Learning
â€¢ Types of Machine Learning
â€¢ Importance of ML
Applications of Machine Learning in Cybersecurity
â€¢ Malicious Website Classification
â€¢ Android Malware Detection
â€¢ Fake News Detection
Registration Link: https://www.infosectrain.com/events/machine-learning-for-cybersecurity-bootcamp-by-nawaj/
About Infosec Train
InfosecTrain is a prominent security and technology training and consulting organization that offers a wide range of IT security services and training. InfosecTrain was created in 2016 by a group of eager and seasoned industry veterans with a combined experience of over 15 years.
To know more about training programs offered by Infosec Train:
Please write back to firstname.lastname@example.org or call at IND: 1800-843-7890 (Toll-Free) / US: +1 657-722-11127 / UK: +44 7451 208413