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Microsoft Malware Detection Project Course

4.7/5
4/5

(321 ratings)  2,124 students

Created by Selva Prabhakaran

220,000 +

Professionals Trained

250 +

Workshops every month

70 +

Countries and counting

What you will learn

01

Python Distribution

Anaconda, basic data types, strings, regular expressions, data structures, loops, and control statements.

02

Python Distribution

Anaconda, basic data types, strings, regular expressions, data structures, loops, and control statements.

03

Python Distribution

Anaconda, basic data types, strings, regular expressions, data structures, loops, and control statements.

04

Python Distribution

Anaconda, basic data types, strings, regular expressions, data structures, loops, and control statements.

05

Python Distribution

Anaconda, basic data types, strings, regular expressions, data structures, loops, and control statements.

06

Python Distribution

Anaconda, basic data types, strings, regular expressions, data structures, loops, and control statements.

Course Curriculum

11 Sections • 33 Lectures • 4h 51 min total length

Learning Objective of the Course

03.50
 

Problem Description

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05.01

Learning Objective of the Course

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03.50

Problem Description

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05.01

Learning Objective of the Course

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03.50

Problem Description

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05.01

Learning Objective of the Course

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03.50

Problem Description

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05.01

Learning Objective of the Course

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03.50

Problem Description

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05.01

Learning Objective of the Course

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03.50

Problem Description

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05.01

Requirements

Who should attend this course?

About the course

Malware attacks affect not just individual consumers, but also enterprises and governments. And as a provider of operating system software, Microsoft takes this problem very seriously.
In this course you will solve this problem by predicting whether a computer is going to be attacked by malware or not. You’ll learn end-to-end project steps, in-depth concepts, real world tips and tricks, and the full code involved in building the actual data science solution.
You will learn the following skills by the end of the course:
LightGBM XGBoost Random Forest Decision Tree Logistic Regression Hyperparameter Tuning Feature Importance Confusion Matrix ROC AUC Concordance and Discordance Precision Recall Curve Capture Rates and Gains Feature Engineering Label Encoding Frequency Encoding Chi-Square test ANOVA test Exploratory Data Analysis Memory Optimization Data Preprocessing

Instructor

Selva Prabhakaran

Selva Prabhakaran

Principal Data Scientist

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4.5
Instructor rating

2,343
reviews

102,432
students

9
Courses

What Learners Are Saying

Ong Chu Feng

Data Analyst
4/5
The content was sufficient and the trainer was well-versed in the subject. Not only did he ensure that we understood the logic behind every step, he always used real-life examples to make it easier for us to understand. Moreover, he spent additional time to let us consult him on Data Science-related matters outside the curriculum. He gave us advice and extra study materials to enhance our understanding. Thanks, Knowledgehut!a
Attended Data Science with Python Certification workshop in January 2020

Ong Chu Feng

Data Analyst
4/5
The content was sufficient and the trainer was well-versed in the subject. Not only did he ensure that we understood the logic behind every step, he always used real-life examples to make it easier for us to understand. Moreover, he spent additional time to let us consult him on Data Science-related matters outside the curriculum. He gave us advice and extra study materials to enhance our understanding. Thanks, Knowledgehut!a
Attended Data Science with Python Certification workshop in January 2020

Ong Chu Feng

Data Analyst
4/5
The content was sufficient and the trainer was well-versed in the subject. Not only did he ensure that we understood the logic behind every step, he always used real-life examples to make it easier for us to understand. Moreover, he spent additional time to let us consult him on Data Science-related matters outside the curriculum. He gave us advice and extra study materials to enhance our understanding. Thanks, Knowledgehut!a
Attended Data Science with Python Certification workshop in January 2020

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FAQs

This is a completely self-paced online project course – you decide when you start and when you finish. On an average, students have finished this project course in 2-3 weeks.
This is a completely self-paced online project course – you decide when you start and when you finish. On an average, students have finished this project course in 2-3 weeks.
This is a completely self-paced online project course – you decide when you start and when you finish. On an average, students have finished this project course in 2-3 weeks.
This is a completely self-paced online project course – you decide when you start and when you finish. On an average, students have finished this project course in 2-3 weeks.
This is a completely self-paced online project course – you decide when you start and when you finish. On an average, students have finished this project course in 2-3 weeks.
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Machine Learning A-Z™: Hands-On Python & R In Data Science