COURSE
INTRODUCTION

Course Description

Currently, Machine learning is the hottest skill in the job market. Like many other domains, Machine Learning has many use cases in Cyber Security domain. Most of  Security Operation engineers deal with massive amount of data in terms logs getting generated by Firewall, IPS, Anti-Virus, Web Servers, Desktop etc. It is humanly not possible to analyze these data and tell what is going on in the network. One needs to be aware of machine learning sophisticated algorithms to find the needle in a haystack. The best part of Machine learning is not only it helps one Cyber Security Professional to perform reactive analysis but also perform predictive analysis.

Program Benefits Description

Big data skills are required for those you want to understand each deadly attack in its entirety. SOC engineers are required to find out the root cause of any outages and this is where Machine learning skills will be most helpful. If you are working in IRT (Incident Response Team) then you will consume a large amount of data and come up with your own theory about the incident. Those who are responsible for protecting the critical networks are required to have some really good Machine Learning skills in order to predict the attack/outage.

What'll you Learn?
  • Introduction to Machine Learning.
  • Supervised and Unsupervised Learning.
  • Classification Tools and Techniques.
  • Clustering Analysis.
  • Working with Decision trees.
  • Bayesian Algorithms.
  • Hands-on lab with Python, Spark and Machine Learning Library.
Course Pricing Description

To know more about the Program Pricing, just fill the form. One of our representatives will get back to you with the requested information.

COURSE
STRUCTURE

3 Modules Available

Module 1

Machine Learning and Python

  • Working with Python ML Libraries.
  • Writing basic ML programs using Python.

 

Module 2

Supervised Learning

  • Classification and Regression.
  • Generalization, Over/Under fitting.
  • Challenges in Supervised Learning.

 

Module 3

Unsupervised Learning

  • Types of Unsupervised learning.
  • Clustering.
  • Challenges in Unsupervised learning.

Thoughts on Model Improvement.

Need Help

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FREQUENTLY ASKED
QUESTIONS

01 What prior skills required to attend this module?

Yes. This is an advanced course and one need to finish at least Big Data fundamentals and Python course for enrolling in this training program.

02 Will I be able to practice labs once I finish my course?

Yes, you will be provided with all necessary software and documents which will help you explore more about the topic.

03 How many hands-on labs will be there in this course?

Purple Synapz is all about understanding the concepts at very low level and therefore each topic will have their own hands-on labs exercises. Refer Course details for more information.

04 Can I attend this course as an individual module?

Yes, this course is offered as an independent course. For additional information, talk to our Support Team.