Machine Learning & Deep Learning in Python & R- (Free Course)


What you’ll learn

  1. Learn how to solve real-world problems using machine-learning techniques
  2. Machine learning models such as linear regression, logistic regression, ANN, etc.
  3. Advanced machine learning models such as Decision Trees, XGBoost, Random Forest, SVM and others.
  4. Understand the basics of statistics and machine learning concepts
  5. How to perform basic statistical operations and run ML models in Python
  6. Extensive knowledge of data acquisition and data preprocessing for machine learning problems
  7. How to turn a business problem into a machine learning problem

This course includes:

  • 33 hours on-demand video
  • 4 articles
  • 4 downloadable resources
  • Access on mobile and TV
  • Certificate of completion


Are you looking for a comprehensive Machine Learning and Deep Learning course that can help you start a successful career in Data Science, Machine Learning, Python, R or Deep Learning?

You’ve found the right machine learning course!


After completing this course you will be able to:

· Confidently build predictive machine learning and deep learning models using R and Python to solve business problems and develop business strategies

· Answer interview questions about Machine Learning, Deep Learning, R, Python

· Enter and appear in online data analysis and data science competitions such as Kaggle competitions

Check out the content below to see what deep learning and machine learning models you will learn.

How will this course help you?

A verifiable certificate of course completion will be issued to all participants of this machine learning foundational course.

If you are a CEO or executive, or a student looking to study machine learning and deep learning concepts and apply them to real-world business problems, this course will give you a solid foundation to do so by teaching you the most popular machine learning and deep learning techniques. You will also gain access to data science and data analysis tools such as R and Python.

Why should you choose this course?

This course covers all the steps you need to take to solve business problems using linear regression. It also focuses on machine learning and deep learning techniques in R and Python.

Most courses only focus on teaching how to do data analysis, but we believe that what happens before and after doing data analysis is even more important. Before starting data analysis, it is very important to have the right data and process it first. And once you’ve done data analysis, you should be able to assess the quality of your model and interpret the results so you can actually help your business. This is where machine learning and deep learning come into play. Knowledge of data analysis tools like R, Python plays an important role in this field of machine learning and deep learning.

What qualifies us to teach you?

This course is taught by Abhishek and Pukhraj. As managers of consulting firm Global Analytics, we have helped companies solve their business problems using machine learning techniques and used our experience to bring practical aspects of data analysis to this course. We have deep knowledge of machine learning and deep learning techniques using data science and data analysis tools R, Python.

We’re also makers of some of the most popular online courses – with over 600,000 registrations and thousands of 5-star reviews like these:

It was very good, I like the fact that all the explanations can be understood by a layman – Joshua

Thanks to the authors for this excellent course. They are the best and this course is worth every price. – Daisies

Our promise

How to Get this course FREE?

Note: The udemy Courses Will be free for a Maximum of 1000 Learners can use the promo code AND Get this course 100% Free. After that, you will get this course at a discounted price. (Still, It’s a good deal for you to get this course at a discounted price).

External links may contain affiliate links, meaning we get a commission if you decide to make a purchase. Read our disclosure.

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