Udemy

Machine Learning Practical: 6 Real-World Applications

Enroll Now
  • 24,597 Students
  • Updated 1/2025
4.5
(3,184 Ratings)
CTgoodjobs selects quality courses to enhance professionals' competitiveness. By purchasing courses through links on our site, we may receive an affiliate commission.

Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
8 Hour(s) 36 Minute(s)
Language
English
Taught by
SuperDataScience Team, Rony Sulca, Ligency ​
Rating
4.5
(3,184 Ratings)
2 views

Course Overview

Machine Learning Practical: 6 Real-World Applications

Machine Learning - Get Your Hands Dirty by Solving Real Industry Challenges with Python

So you know the theory of Machine Learning and know how to create your first algorithms. Now what? 

There are tons of courses out there about the underlying theory of Machine Learning which don’t go any deeper – into the applications.


This course is not one of them.

Are you ready to apply all of the theory and knowledge to real life Machine Learning challenges?  

Then welcome to “Machine Learning Practical”.


We gathered best industry professionals with tons of completed projects behind.

Each presenter has a unique style, which is determined by his experience, and like in a real world, you will need adjust to it if you want successfully complete this course. We will leave no one behind!


This course will demystify how real Data Science project looks like. Time to move away from these polished examples which are only introducing you to the matter, but not giving any real experience.


If you are still dreaming where to learn Machine Learning through practice, where to take real-life projects for your CV, how to not look like a noob in the recruiter's eyes, then you came to the right place!


This course provides a hands-on approach to real-life challenges and covers exactly what you need to succeed in the real world of Data Science.

 

There are most exciting case studies including:

●      diagnosing diabetes in the early stages

●      directing customers to subscription products with app usage analysis

●      minimizing churn rate in finance

●      predicting customer location with GPS data

●      forecasting future currency exchange rates

●      classifying fashion

●      predicting breast cancer

●      and much more!

 

All real.

All true.

All helpful and applicable.

And another extra:

 

In this course we will also cover Deep Learning Techniques and their practical applications.

So as you can see, our goal here is to really build the World’s leading practical machine learning course.

If your goal is to become a Machine Learning expert, you know how valuable these real-life examples really are. 

They will determine the difference between Data Scientists who just know the theory and Machine Learning experts who have gotten their hands dirty.

So if you want to get hands-on experience which you can add to your portfolio, then this course is for you.

Enroll now and we’ll see you inside.

Course Content

  • 8 section(s)
  • 81 lecture(s)
  • Section 1 Introduction
  • Section 2 Breast Cancer Classification
  • Section 3 Fashion Class Classification
  • Section 4 Directing Customers to Subscription Through App Behavior Analysis
  • Section 5 Minimizing Churn Rate Through Analysis of Financial Habits
  • Section 6 Predicting the Likelihood of E-Signing a Loan Based on Financial History
  • Section 7 Credit Card Fraud Detection
  • Section 8 Congratulations!! Don't forget your Prize :)

What You’ll Learn

  • You will know how real data science project looks like
  • You will be able to include these Case Studies in your resume
  • You will be able better market yourself as a Machine Learning Practioneer
  • You will feel confident during Data Science interview
  • You will learn how to chain multiple ML algorithms together to achieve the goal
  • You will learn most advanced Data Visualization techniques with Seaborn and Matplotlib
  • You will learn Logistic Regression
  • You will learn L1 Regularization (Lasso)
  • You will learn Random Forest Classifier

Reviews

  • K
    Krisna Dwipayana
    1.0

    Hello, First, I wanted to say that this course is absolutely wonderful. I have learned so much about data science and feel that I truly understand the material thanks to your teaching. However, I am encountering one issue. I am trying to access the course materials section that contains the files and program code, but I am unable to access it. It seems the link is broken or leading to an error. Could you please advise me on how I can access these materials? Thank you for your help and for the fantastic course.

  • Q
    Quoc Viet Nguyen
    3.5

    overall i did learn a lot of new things that they would not teach at the university however the instructor's would code without too detailed explanation on what the lines do and how we can understand them. but overall well paced and good for people that want more experience in ML projects

  • N
    Nikkie Yiokari
    5.0

    clear to understand

  • M
    Mahema Rooda
    4.0

    NA

Start FollowingSee all

We use cookies to enhance your experience on our website. Please read and confirm your agreement to our Privacy Policy and Terms and Conditions before continue to browse our website.

Read and Agreed