In no other project course, you will find such detailed mathematics behind the concepts ” – Abhishek

Microsoft Malware Detection Project Course

Predict whether a system will get infected by malware or not. Work on real Microsoft data, solve data challenges, gather insights, build and evaluate

4.7

4.7/5

(321 ratings)

2,124 students

“In no other project course, you will find such detailed mathematics behind the concepts” – Abhishek

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Microsoft Malware Detection Project Course

Predict whether a system will get infected by malware or not. Work on real Microsoft data, solve data challenges, gather insights, build and evaluate models just like a practising data scientist on the  project

4.5

4.5/5

(321 ratings)

2,124 students

$28

30-Day Money Back Guarantee

What you'll learn

This course includes

What you'll learn

$28

30-Day Money Back Guarantee

Course Curriculum

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

     Learning Objective of the Course

03.50

     Problem Description

 Preview       05.01

     Need for EDA

04.46

     Exploratory Data Analysis Part 1

14.26

     Exploratory Data Analysis Part 2

13.14

     Chi Squared Test Theory and Maths

17.47

     Chi Squared Test and Odds Ratio Demo

09.09

     ANOVA Theory and Math

22.42

     ANOVA Demo

06.30

     Confusion Matrix and Evaluation Metrics

10.05

     Concordance and Discordance

09.18

     ROC Curve

09.22

     Precision Recall Curve

02.53

     Evaluation Metrics Demo

05.12

     Capture Rates and Gains

07.54

     Decision Trees and Improvements

17.11

     Random Forests

08.51

     XGBoost

07.25

     LightGBM

07.38

     Tuning Hyper-Parameters

07.20

     Feature Importance

11.05

     Feature Importance - Demo

01.45

     Final Words

01.28

Requirements

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

Who is this course for

Instructor

Selva Prabhakaran

Principal Data Scientist

My name is Selva, and I am super excited to mentor you on this project!

I head the Data Science team for a global Fortune 500 company and over the last 10 years of my data science experience I’ve deployed 20+ global products. I’m also the Founder & Chief Author of Machine Learning Plus, which has over 4M annual readers.

I specialize in covering the in-depth intuition and maths of any concept or algorithm. And based on my existing student request, I’ve put up the series of project courses with detailed explanations – just like an on the job experience. Hope you love it!

Student Reviews

Lorenna Christina

Lorenna Chrisitina

The instructor has a wide range of knowledge What I liked most about the classes is how the instructor explained the mathematics behind the algorithms easily, which in turn makes the course more interesting. I definitely recommend this project!

Moinak Dey

Moinak Dey

Data Science could not have been explained easier than this. All the major algorithms were explained beautifully from scratch and the practical tips are noteworthy as well.

Jyoti Goyal

Jyoti Goyal

Loved the way the course guided me through the entire project solving journey. Helped build my confidence for end-to-end implementation

Souptik Dhar

Souptik Dhar

I was able to get a first hand feel of solving a project with large amounts of data and multiple modeling techniques, just like a work-experience

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.

If you are a data science aspirant preparing to break into role of data scientist or if you are a data scientist trying to get work equivalent experience in a new domain, this project course is for you. Check our pre-requisites section for more details.

Yes, all data, python codes and notebooks are shared as downloadable resources within the course

You will have access to the video course access for 1 year. You can retain the downloadable content (i.e. complete dataset, Jupyter notebooks and codes) forever.

Yes, you will get certification of project completion, which will also mention the steps of the project that you’ve solved.

Every lecture has a comment section. You can write your question in the comments, and the instructor and the team will get back to you.  You can also check other students’ comments to check if it has already been asked and answered.

We  are confident about our content and are sure that you’ll find value in it. However, in case you are unhappy with the course, you can drop a mail to [email protected] in the first 30 days, and we will give you a full refund.

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